diff --git "a/exgra-med-gpt-medrag-only/log.txt" "b/exgra-med-gpt-medrag-only/log.txt"
new file mode 100644--- /dev/null
+++ "b/exgra-med-gpt-medrag-only/log.txt"
@@ -0,0 +1,10957 @@
+2025-09-22 23:31:05 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'visual_projection.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 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+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:05 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 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'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:05 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:31:05 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:31:06 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'visual_projection.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_projection.weight', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 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'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.weight']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:06 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'visual_projection.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 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'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.weight']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:06 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:31:06 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:31:09 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_projection.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.4.layer_norm1.bias', 'logit_scale', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 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'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 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'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'visual_projection.weight', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:09 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_projection.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 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'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:09 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:31:09 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:31:11 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 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'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'logit_scale', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:11 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'visual_projection.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'logit_scale', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:31:11 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:31:11 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:33:26 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv2.lin_rel.weight', 'model.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv1.lin_rel.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:26 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv2.lin_rel.weight', 'model.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv1.lin_rel.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:26 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_root.weight', 'model.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_rel.bias']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:26 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_root.weight', 'model.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_rel.bias']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:27 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.bias', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:27 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.bias', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:27 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.bias', 'model.message_pass_node_features.conv2.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:27 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.bias', 'model.message_pass_node_features.conv2.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:33:40 | INFO | wandb | Current SDK version is 0.16.1
+2025-09-22 23:33:40 | INFO | wandb | Configure stats pid to 136273
+2025-09-22 23:33:40 | INFO | wandb | Loading settings from /root/.config/wandb/settings
+2025-09-22 23:33:40 | INFO | wandb | Loading settings from /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/settings
+2025-09-22 23:33:40 | INFO | wandb | Loading settings from environment variables: {'api_key': '***REDACTED***', 'project': 'llava_med'}
+2025-09-22 23:33:40 | INFO | wandb | Inferring run settings from compute environment: {'program_relpath': 'llava/train/train_mem_CoT.py', 'program_abspath': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/llava/train/train_mem_CoT.py', 'program': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/llava/train/train_mem_CoT.py'}
+2025-09-22 23:33:40 | INFO | wandb | Applying login settings: {'api_key': '***REDACTED***'}
+2025-09-22 23:33:40 | INFO | wandb | Applying login settings: {'api_key': '***REDACTED***'}
+2025-09-22 23:33:40 | INFO | wandb | Logging user logs to /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/run-20250922_233340-h9abynjz/logs/debug.log
+2025-09-22 23:33:40 | INFO | wandb | Logging internal logs to /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/run-20250922_233340-h9abynjz/logs/debug-internal.log
+2025-09-22 23:33:40 | INFO | wandb | calling init triggers
+2025-09-22 23:33:40 | INFO | wandb | wandb.init called with sweep_config: {}
+config: {}
+2025-09-22 23:33:40 | INFO | wandb | starting backend
+2025-09-22 23:33:40 | INFO | wandb | setting up manager
+2025-09-22 23:33:40 | INFO | wandb | multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-09-22 23:33:40 | INFO | wandb | backend started and connected
+2025-09-22 23:33:40 | DEBUG | wandb | no default config file found in config-defaults.yaml
+2025-09-22 23:33:40 | INFO | wandb | updated telemetry
+2025-09-22 23:33:40 | INFO | wandb | communicating run to backend with 90.0 second timeout
+2025-09-22 23:33:41 | INFO | wandb | communicating current version
+2025-09-22 23:33:41 | INFO | wandb | got version response upgrade_message: "wandb version 0.22.0 is available!  To upgrade, please run:\n $ pip install wandb --upgrade"
+
+2025-09-22 23:33:41 | INFO | wandb | starting run threads in backend
+2025-09-22 23:33:42 | INFO | wandb | atexit reg
+2025-09-22 23:33:42 | INFO | wandb | redirect: wrap_raw
+2025-09-22 23:33:42 | INFO | wandb | Wrapping output streams.
+2025-09-22 23:33:42 | INFO | wandb | Redirects installed.
+2025-09-22 23:33:42 | INFO | wandb | run started, returning control to user process
+2025-09-22 23:33:42 | INFO | wandb | config_cb None None {'vocab_size': 32004, 'hidden_size': 4096, 'intermediate_size': 11008, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-06, 'use_cache': False, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'chunk_size_feed_forward': 0, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['LlavaLlamaForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 0, 'pad_token_id': -1, 'eos_token_id': 1, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix', 'transformers_version': '4.28.0.dev0', 'freeze_mm_mlp_adapter': False, 'graph_num_features': 4096, 'max_sequence_length': 2048, 'mm_hidden_size': 1024, 'mm_projector_type': 'mlp2x_gelu', 'mm_use_im_start_end': True, 'mm_vision_select_layer': -2, 'mm_vision_tower': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14', 'model_type': 'llava', 'more_mlp': False, 'multi_graph': True, 'remove_graph': False, 'tune_mm_mlp_adapter': False, 'unify': True, 'use_mm_proj': True, 'output_dir': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/weights_finetuned/CoT-100_exgra_med_on_No_CoT_dataset_epochs4_batchsize8_prompt_mode_simple_use_ragtrue_contrastivefalse_after_defalse_detachfalse_newFormat', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': False, 'do_predict': False, 'evaluation_strategy': 'no', 'prediction_loss_only': False, 'per_device_train_batch_size': 8, 'per_device_eval_batch_size': 4, 'per_gpu_train_batch_size': 'None', 'per_gpu_eval_batch_size': 'None', 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': 'None', 'eval_delay': 0, 'learning_rate': 2e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 4.0, 'max_steps': -1, 'lr_scheduler_type': 'cosine', 'warmup_ratio': 0.03, 'warmup_steps': 0, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/weights_finetuned/CoT-100_exgra_med_on_No_CoT_dataset_epochs4_batchsize8_prompt_mode_simple_use_ragtrue_contrastivefalse_after_defalse_detachfalse_newFormat/runs/Sep22_23-29-39_serv-3333', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 1, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 101100, 'save_total_limit': 4, 'save_on_each_node': False, 'no_cuda': False, 'use_mps_device': False, 'seed': 42, 'data_seed': 'None', 'jit_mode_eval': False, 'use_ipex': False, 'bf16': True, 'fp16': False, 'fp16_opt_level': 'O1', 'half_precision_backend': 'cuda_amp', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': True, 'local_rank': 0, 'xpu_backend': 'None', 'tpu_num_cores': 'None', 'tpu_metrics_debug': False, 'debug': '[]', 'dataloader_drop_last': False, 'eval_steps': 'None', 'dataloader_num_workers': 0, 'past_index': -1, 'run_name': 'stage2_exgra_med_on_No_CoT_dataset_epochs4_batchsize8_prompt_mode_simple_use_ragtrue_contrastivefalse_after_defalse_detachfalse_newFormat', 'disable_tqdm': False, 'remove_unused_columns': False, 'label_names': 'None', 'load_best_model_at_end': False, 'metric_for_best_model': 'None', 'greater_is_better': 'None', 'ignore_data_skip': False, 'sharded_ddp': '[]', 'fsdp': "['full_shard', 'auto_wrap']", 'fsdp_min_num_params': 0, 'fsdp_config': "{'fsdp_min_num_params': 0, 'fsdp_transformer_layer_cls_to_wrap': ['LlamaDecoderLayer'], 'xla': False, 'xla_fsdp_grad_ckpt': False}", 'fsdp_transformer_layer_cls_to_wrap': 'LlamaDecoderLayer', 'deepspeed': 'None', 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': 'None', 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': "['wandb']", 'ddp_find_unused_parameters': 'None', 'ddp_bucket_cap_mb': 'None', 'dataloader_pin_memory': True, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': 'None', 'hub_model_id': 'None', 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'gradient_checkpointing': True, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': 'None', 'push_to_hub_organization': 'None', 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': 'None', 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': 'None', 'torch_compile_mode': 'None', 'cache_dir': 'None', 'force_fsdp': False, 'model_max_length': 4096, 'train_batch_size': 8, 'eval_batch_size': 4}
+2025-09-22 23:54:02 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 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'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'visual_projection.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'logit_scale', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.10.mlp.fc2.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:02 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.9.mlp.fc1.weight', 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'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 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'text_model.encoder.layers.11.self_attn.k_proj.bias', 'logit_scale', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.10.mlp.fc2.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:02 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:54:02 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:54:02 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.5.layer_norm1.weight', 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'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'visual_projection.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 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'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'logit_scale', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:02 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 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'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'logit_scale', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:02 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:54:02 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:54:03 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 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'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:03 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_projection.weight', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'visual_projection.weight', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'logit_scale', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:03 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:54:03 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:54:07 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'logit_scale', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 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'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 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'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.9.layer_norm1.weight', 'visual_projection.weight', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.final_layer_norm.weight']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:07 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'logit_scale', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.9.layer_norm1.weight', 'visual_projection.weight', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.final_layer_norm.weight']
+- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:54:08 | INFO | LVLM-Med | projector_type: mlp2x_gelu
+2025-09-22 23:54:08 | INFO | LVLM-Med | --------------------------This is version 1.5---------------------
+2025-09-22 23:56:30 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv2.lin_root.weight', 'model.bias', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:30 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv2.lin_root.weight', 'model.bias', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:45 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:45 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv2.lin_rel.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:45 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.bias', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:45 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.bias', 'model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_root.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:46 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.bias', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:46 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/models/checkpoint_llava_med_instruct_60k_inline_mention_version_1-5_1e0_multi_graph_100_scale_test_bugfix were not used when initializing LlavaLlamaForCausalLM: ['model.message_pass_node_features.conv1.lin_rel.weight', 'model.message_pass_node_features.conv1.lin_rel.bias', 'model.message_pass_node_features.conv2.lin_rel.weight', 'model.bias', 'model.message_pass_node_features.conv2.lin_rel.bias', 'model.message_pass_node_features.conv1.lin_root.weight', 'model.message_pass_node_features.conv2.lin_root.weight']
+- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
+- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
+2025-09-22 23:56:57 | INFO | wandb | Current SDK version is 0.16.1
+2025-09-22 23:56:57 | INFO | wandb | Configure stats pid to 159158
+2025-09-22 23:56:57 | INFO | wandb | Loading settings from /root/.config/wandb/settings
+2025-09-22 23:56:57 | INFO | wandb | Loading settings from /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/settings
+2025-09-22 23:56:57 | INFO | wandb | Loading settings from environment variables: {'api_key': '***REDACTED***', 'project': 'llava_med'}
+2025-09-22 23:56:57 | INFO | wandb | Inferring run settings from compute environment: {'program_relpath': 'llava/train/train_mem.py', 'program_abspath': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/llava/train/train_mem.py', 'program': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/llava/train/train_mem.py'}
+2025-09-22 23:56:57 | INFO | wandb | Applying login settings: {'api_key': '***REDACTED***'}
+2025-09-22 23:56:57 | INFO | wandb | Applying login settings: {'api_key': '***REDACTED***'}
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+2025-09-22 23:56:57 | INFO | wandb | Logging internal logs to /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/run-20250922_235657-avnql2xp/logs/debug-internal.log
+2025-09-22 23:56:57 | INFO | wandb | calling init triggers
+2025-09-22 23:56:57 | INFO | wandb | wandb.init called with sweep_config: {}
+config: {}
+2025-09-22 23:56:57 | INFO | wandb | starting backend
+2025-09-22 23:56:57 | INFO | wandb | setting up manager
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+2025-09-22 23:56:57 | INFO | wandb | backend started and connected
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+2025-09-22 23:56:57 | INFO | wandb | updated telemetry
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+2025-09-22 23:56:58 | INFO | wandb | communicating current version
+2025-09-22 23:56:58 | INFO | wandb | got version response upgrade_message: "wandb version 0.22.0 is available!  To upgrade, please run:\n $ pip install wandb --upgrade"
+
+2025-09-22 23:56:58 | INFO | wandb | starting run threads in backend
+2025-09-22 23:56:58 | INFO | wandb | atexit reg
+2025-09-22 23:56:58 | INFO | wandb | redirect: wrap_raw
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'mm_projector_type': 'mlp2x_gelu', 'mm_use_im_start_end': True, 'mm_vision_select_layer': -2, 'mm_vision_tower': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14', 'model_type': 'llava', 'more_mlp': False, 'multi_graph': True, 'remove_graph': False, 'tune_mm_mlp_adapter': False, 'unify': True, 'use_mm_proj': True, 'output_dir': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/weights_finetuned/CoT-100_exgra_med_on_No_CoT_dataset_epochs4_batchsize8_prompt_mode_simple_use_ragtrue_contrastivefalse_after_defalse_detachfalse_newFormat', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': False, 'do_predict': False, 'evaluation_strategy': 'no', 'prediction_loss_only': False, 'per_device_train_batch_size': 8, 'per_device_eval_batch_size': 4, 'per_gpu_train_batch_size': 'None', 'per_gpu_eval_batch_size': 'None', 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': 'None', 'eval_delay': 0, 'learning_rate': 2e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 4.0, 'max_steps': -1, 'lr_scheduler_type': 'cosine', 'warmup_ratio': 0.03, 'warmup_steps': 0, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/weights_finetuned/CoT-100_exgra_med_on_No_CoT_dataset_epochs4_batchsize8_prompt_mode_simple_use_ragtrue_contrastivefalse_after_defalse_detachfalse_newFormat/runs/Sep22_23-52-35_serv-3333', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 1, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 101100, 'save_total_limit': 4, 'save_on_each_node': False, 'no_cuda': False, 'use_mps_device': False, 'seed': 42, 'data_seed': 'None', 'jit_mode_eval': False, 'use_ipex': False, 'bf16': True, 'fp16': False, 'fp16_opt_level': 'O1', 'half_precision_backend': 'cuda_amp', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': True, 'local_rank': 0, 'xpu_backend': 'None', 'tpu_num_cores': 'None', 'tpu_metrics_debug': False, 'debug': '[]', 'dataloader_drop_last': False, 'eval_steps': 'None', 'dataloader_num_workers': 0, 'past_index': -1, 'run_name': 'stage2_exgra_med_on_No_CoT_dataset_epochs4_batchsize8_prompt_mode_simple_use_ragtrue_contrastivefalse_after_defalse_detachfalse_newFormat', 'disable_tqdm': False, 'remove_unused_columns': False, 'label_names': 'None', 'load_best_model_at_end': False, 'metric_for_best_model': 'None', 'greater_is_better': 'None', 'ignore_data_skip': False, 'sharded_ddp': '[]', 'fsdp': "['full_shard', 'auto_wrap']", 'fsdp_min_num_params': 0, 'fsdp_config': "{'fsdp_min_num_params': 0, 'fsdp_transformer_layer_cls_to_wrap': ['LlamaDecoderLayer'], 'xla': False, 'xla_fsdp_grad_ckpt': False}", 'fsdp_transformer_layer_cls_to_wrap': 'LlamaDecoderLayer', 'deepspeed': 'None', 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': 'None', 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+2025-09-22 23:57:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.8418145179748535 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.0002946853637695 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.793118953704834 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.784578323364258 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.743396282196045 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.0334553718566895 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.892551898956299 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.824793338775635 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.312119007110596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.3295207023620605 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.184696674346924 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.568771839141846 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.109098434448242 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.1902852058410645 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.226193904876709 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.2968828678131104 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.247319221496582 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2158054113388062 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3073736429214478 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3164868354797363 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.9752745032310486 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0019794702529907 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.9123373627662659 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.6805939078330994 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.6745705604553223 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.4670085906982422 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3303734064102173 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.7414489388465881 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.652340829372406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.8029395341873169 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5294592976570129 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5692140460014343 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5075675249099731 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.4484017491340637 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5102523565292358 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5053359270095825 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2993265986442566 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3692716658115387 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.42888495326042175 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3818396329879761 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13916832208633423 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.12422159314155579 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.11872807890176773 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1798541247844696 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1867246925830841 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.4118874669075012 | lossAlign: 0
+2025-09-22 23:58:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18346552550792694 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2898622751235962 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.052518706768751144 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23744021356105804 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1486518830060959 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1602165699005127 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3081284761428833 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.4124453067779541 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.410891592502594 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07930093258619308 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15759816765785217 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16916128993034363 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.10471836477518082 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.12611976265907288 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.11287877708673477 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06175121292471886 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05712759867310524 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06396713107824326 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06391903012990952 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05843589827418327 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.051172226667404175 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06756693869829178 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06603744626045227 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03918386995792389 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0534956157207489 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05346072465181351 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05484878271818161 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.09514745324850082 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.11404360085725784 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.10608525574207306 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16368132829666138 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06920492649078369 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13514932990074158 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06919419020414352 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04510052502155304 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07105454057455063 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13724680244922638 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06713741272687912 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1623212844133377 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.11014354228973389 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0891960933804512 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08157507330179214 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06754037737846375 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.050782810896635056 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.09492111951112747 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0606546588242054 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08289596438407898 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.051582470536231995 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05615827813744545 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028767185285687447 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05428816378116608 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.044532064348459244 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03658765181899071 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06572026759386063 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025077633559703827 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08741815388202667 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0505264587700367 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07684396207332611 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07486899942159653 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04800819605588913 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06882093101739883 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07556600123643875 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0659547671675682 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0322277806699276 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.10769806802272797 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010388711467385292 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06211228668689728 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05492387339472771 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08024188131093979 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08481217175722122 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01300903968513012 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03283890709280968 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0544927604496479 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03613463044166565 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0346149243414402 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04425547271966934 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.054766833782196045 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05186837166547775 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07089553028345108 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05521756410598755 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06918971240520477 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.053194377571344376 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07041891664266586 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05921877548098564 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05920615419745445 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08086579293012619 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06716398149728775 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05904872715473175 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05832929164171219 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04458317905664444 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06666374206542969 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08865392208099365 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04691905900835991 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05144154280424118 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.062325116246938705 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03763801231980324 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039772115647792816 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0466199591755867 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024884767830371857 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030361678451299667 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08847840875387192 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01555650308728218 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03207087516784668 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004110707901418209 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04613862559199333 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0622267909348011 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.051303714513778687 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05760517343878746 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020940544083714485 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015816137194633484 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01529961172491312 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08483046293258667 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05085410177707672 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.032290536910295486 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04801693186163902 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03514506295323372 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05509212985634804 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0831146389245987 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024148527532815933 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05301423370838165 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.036147840321063995 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03102494403719902 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06171499937772751 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03923661634325981 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.032445814460515976 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04000323638319969 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039815742522478104 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033674661070108414 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06800463050603867 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026023514568805695 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039931148290634155 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011703427881002426 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03566644340753555 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04432188719511032 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.046785127371549606 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039603907614946365 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0378277488052845 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02523967996239662 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039987124502658844 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07226184755563736 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014418640173971653 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03136187791824341 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.053653523325920105 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0039027719758450985 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02166261337697506 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014586949720978737 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07540866732597351 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02841924875974655 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05402069911360741 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06800065189599991 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.031491395086050034 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011334727518260479 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03659934177994728 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.09278278052806854 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03583875298500061 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018418343737721443 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.062239665538072586 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06297951191663742 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01488997507840395 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05039601773023605 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0374399796128273 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04188010096549988 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.036482349038124084 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025395074859261513 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.031515687704086304 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.044440858066082 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04183619096875191 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04415934905409813 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.040144771337509155 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.053532667458057404 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.044584721326828 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.023533185943961143 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029679588973522186 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02740713208913803 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024133170023560524 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04348140209913254 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0671621561050415 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06192878261208534 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04442085325717926 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028872519731521606 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02334653027355671 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022631533443927765 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04895411431789398 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06252682954072952 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0634489580988884 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04198407381772995 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05173748731613159 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03381160646677017 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015012332238256931 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02965940162539482 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.053102653473615646 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.044729556888341904 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.031114477664232254 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019516976550221443 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04219997674226761 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0437026210129261 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004386377055197954 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00953431986272335 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04188986495137215 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009138860739767551 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02878960222005844 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03617000952363014 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02350790612399578 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02903440035879612 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04209338501095772 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.032022517174482346 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033911608159542084 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03929871320724487 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025826402008533478 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03856821730732918 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04104790836572647 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.023336464539170265 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019157009199261665 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030279481783509254 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019728995859622955 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03156327083706856 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.038762178272008896 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04306786507368088 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0342918261885643 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03232637792825699 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027659540995955467 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02205790765583515 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004763483069837093 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03364862874150276 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03829529508948326 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006058232393115759 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.021855944767594337 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.023695699870586395 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05482490733265877 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03073103539645672 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029522044584155083 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.08533209562301636 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00828498974442482 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026392921805381775 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.021840406581759453 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04050903394818306 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012956727296113968 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028699368238449097 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0275593064725399 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04366392642259598 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010509436018764973 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04489336907863617 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033234886825084686 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026821771636605263 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04821917414665222 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003549674991518259 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026787161827087402 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029279787093400955 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009462622925639153 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030652785673737526 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04025763273239136 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010107849724590778 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027784934267401695 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007596958894282579 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009472447447478771 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04053486883640289 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011583765037357807 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004641289822757244 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035524184349924326 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012153957970440388 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022858619689941406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028252502903342247 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011917509138584137 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0033531745430082083 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018094979226589203 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02569427527487278 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010917427949607372 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013045291416347027 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03311124071478844 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01216292753815651 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017223620787262917 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.035570453852415085 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0073064155876636505 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03458098694682121 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024883046746253967 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007800256367772818 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020875655114650726 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01177153643220663 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004159625619649887 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029013698920607567 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003167447168380022 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002389825414866209 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013490757904946804 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017266955226659775 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014496963704004884 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012396322563290596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028551947325468063 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05325745418667793 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006219787988811731 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018556172028183937 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05664089694619179 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04570993408560753 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01787794753909111 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02965773083269596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03515436500310898 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007461936213076115 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02123871259391308 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007542825303971767 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020574290305376053 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0448574461042881 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.038333959877491 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04218680411577225 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015998773276805878 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007029018830507994 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018400967121124268 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.044794611632823944 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008360633626580238 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016621200367808342 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01768054999411106 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04914015159010887 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027335310354828835 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.053237441927194595 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029018670320510864 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012986276298761368 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02600955404341221 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03108186274766922 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006719871889799833 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020679594948887825 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012955811806023121 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019204162061214447 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027735404670238495 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014076342806220055 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022321810945868492 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007986375130712986 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03665383905172348 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06508100032806396 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017098091542720795 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.035523395985364914 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024327997118234634 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01896681636571884 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01632869616150856 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030875368043780327 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018778201192617416 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025367973372340202 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.021061185747385025 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014482912607491016 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011503336019814014 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01988494023680687 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016297239810228348 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008683610707521439 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03557981178164482 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.038993898779153824 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0062060365453362465 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00523334089666605 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02567273937165737 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015976933762431145 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009352562949061394 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024877622723579407 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039574913680553436 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008298533037304878 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004483823664486408 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011487738229334354 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005955955479294062 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026377828791737556 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017391812056303024 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05722213536500931 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.032346904277801514 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020880214869976044 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011355113238096237 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007862023077905178 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035174896474927664 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03201699256896973 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02647620625793934 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02576640248298645 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014172159135341644 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00855955109000206 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05316998437047005 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013617868535220623 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009111852385103703 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0039919111877679825 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01455017551779747 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022720415145158768 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025141797959804535 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011349420063197613 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007024520076811314 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.034512702375650406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020075807347893715 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02374042570590973 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00999034196138382 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01575072482228279 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009687693789601326 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039519619196653366 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012037738226354122 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007499274332076311 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010567644611001015 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.032141972333192825 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011382256634533405 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01109172124415636 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034709505271166563 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027573350816965103 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014567587524652481 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009326264262199402 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009094994515180588 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01761000044643879 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012341918423771858 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013659185729920864 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005091245286166668 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005483652930706739 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01062170322984457 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013660870492458344 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05625949427485466 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024569164961576462 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029560089111328125 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020020022988319397 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03492999076843262 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03337749093770981 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04683079570531845 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001702055218629539 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05011832341551781 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030414711218327284 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007479044143110514 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027139347046613693 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007065116427838802 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027320191264152527 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010186266154050827 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015530839562416077 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04444124549627304 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016507228836417198 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005679399706423283 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01918785274028778 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04381384328007698 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01688414067029953 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003739224513992667 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011013821698725224 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03274465724825859 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01296150777488947 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006849003490060568 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003206117544323206 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002335327211767435 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026984598953276873 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.049811746925115585 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.038703229278326035 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034736725501716137 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007479250896722078 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004232725594192743 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02090326137840748 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003512035356834531 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031063538044691086 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0023080080281943083 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028161155059933662 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007567169144749641 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009110529907047749 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013755819760262966 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0032058877404779196 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015987036749720573 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00550458487123251 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017562026157975197 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007727418094873428 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027413482312113047 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019002897664904594 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030978426802903414 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019521387293934822 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025163762271404266 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0045344955287873745 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006643408909440041 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013199043460190296 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025513935834169388 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004414344672113657 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013525900430977345 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.032416801899671555 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009797925129532814 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0032498259097337723 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012667462229728699 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0020339065231382847 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06112769991159439 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016445084474980831 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03646233677864075 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030461549758911133 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017233356833457947 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0076613170094788074 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006114506628364325 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034845226909965277 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00518200034275651 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014593653380870819 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018980352208018303 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016126099973917007 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015427418984472752 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0024952609091997147 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03261607512831688 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005264406092464924 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014196817763149738 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004857691470533609 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015049944631755352 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02773922123014927 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01091237273067236 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007157290354371071 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012652666307985783 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02201353944838047 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0044120438396930695 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0038635239470750093 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009068779647350311 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011411786079406738 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008466958068311214 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022080782800912857 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010575534775853157 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024038609117269516 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018181748688220978 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005563477985560894 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025722038000822067 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006082639563828707 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002676997799426317 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011501294560730457 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011534040793776512 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007526625879108906 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005799008533358574 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026699122972786427 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014484539860859513 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01918172836303711 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004314167890697718 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005142562091350555 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008756055496633053 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013363638427108526 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02246818318963051 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0529731847345829 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004136368166655302 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006078536622226238 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03975852206349373 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002199252136051655 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004203498363494873 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006802965421229601 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00600640382617712 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010868298821151257 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006361776031553745 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004085171967744827 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.023590508848428726 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012346346862614155 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016993071883916855 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.021956438198685646 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013016654178500175 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01187285128980875 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007011098321527243 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0033520639408379793 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004411070607602596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007204120513051748 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01788128912448883 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0165169108659029 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007605769205838442 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014774251030758023 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015496168285608292 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03901621699333191 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005897989496588707 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014079331420361996 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0032394523732364178 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008487962186336517 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004589966498315334 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00347295799292624 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01882597804069519 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.034023404121398926 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003439253428950906 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001626337761990726 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018246491672471166 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015429888851940632 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0327201709151268 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018513115122914314 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003342550713568926 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.038476306945085526 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006838097237050533 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017103882506489754 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02709241211414337 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03598887473344803 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004305588081479073 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016099194064736366 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034382895100861788 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013163468800485134 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030805140268057585 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010259024798870087 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024880729615688324 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008788716048002243 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008217439753934741 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002024132525548339 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009743072441779077 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022711166820954531 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003855583257973194 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029772876296192408 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011535072699189186 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017214808613061905 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017417166382074356 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002888798713684082 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035842047072947025 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034591439180076122 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006998985540121794 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003977983258664608 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00787615217268467 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03783092275261879 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018339743837714195 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0036373878829181194 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034174369648098946 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0063737547025084496 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022892095148563385 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011866800487041473 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008034405298531055 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014957315288484097 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006871420424431562 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0021882562432438135 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004541353322565556 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002835228107869625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024065250530838966 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006554417312145233 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008556600660085678 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017586197704076767 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002701676683500409 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0043795970268547535 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006217725574970245 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0046639712527394295 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.034495092928409576 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029915668070316315 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0047356016002595425 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030214176513254642 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000914742995519191 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008496978553012013 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003685808042064309 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010812876746058464 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0089694419875741 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005437200888991356 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.07295380532741547 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00325651653110981 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0056724888272583485 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002942254301160574 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002965994644910097 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00671260105445981 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018657436594367027 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010663718916475773 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003814848605543375 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007976996712386608 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.043441686779260635 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009662475436925888 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006366435904055834 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017667142674326897 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04266016557812691 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0038648261688649654 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007082337397150695 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01592376083135605 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001000697142444551 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013892480172216892 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00232454645447433 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010478980839252472 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012964949943125248 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017839651554822922 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0037647937424480915 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010203946381807327 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00332375755533576 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005556677933782339 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005090000340715051 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016788506880402565 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022753330413252115 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0020258300937712193 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012311143800616264 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015726645942777395 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01169524621218443 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04296138882637024 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008421935141086578 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02414936199784279 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01248585619032383 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031913528218865395 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01699700579047203 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01750311069190502 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002987026236951351 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022979095578193665 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024920130148530006 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009082412347197533 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018291643355041742 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013223551213741302 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013443712377920747 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01374727487564087 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003182946238666773 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008951791096478701 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022641640156507492 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026319893077015877 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008264654316008091 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003290056250989437 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02959359623491764 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007554919458925724 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029597539454698563 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002328277565538883 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003800777019932866 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035701680462807417 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01042699720710516 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009041745215654373 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04270375147461891 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015249649295583367 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006890465039759874 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004952341550961137 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0036489840131253004 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018300628289580345 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003934480715543032 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003879542462527752 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012678976636379957 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007524935062974691 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015526555944234133 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016124951653182507 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028914163704030216 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005983145907521248 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014965538866817951 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027536656707525253 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01929870992898941 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01766231656074524 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015398128889501095 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031295940279960632 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02877681888639927 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007168884039856493 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027187480591237545 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001239027245901525 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0055243694223463535 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016638748347759247 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003898701397702098 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01716962642967701 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003679602814372629 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012718194629997015 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033976617851294577 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008020796813070774 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015566488727927208 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008939233608543873 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004911929368972778 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0074755726382136345 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002145726466551423 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03674856945872307 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002568037249147892 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001268508960492909 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035134460777044296 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010791547829285264 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004246852360665798 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007596645154990256 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007787325885146856 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001397615415044129 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006582670845091343 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00675455154851079 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010818333830684423 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0044018859043717384 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029352614656090736 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004443194251507521 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015898618148639798 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018927579512819648 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009295095689594746 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007972140447236598 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019266817718744278 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013996717520058155 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004300410393625498 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006276728585362434 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005120087880641222 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022444571368396282 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000890600320417434 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031942958012223244 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002677507000043988 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.97083809832111e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000585623609367758 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004944568499922752 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006466098129749298 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025387350469827652 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002590767981018871 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0073795318603515625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006916794227436185 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002232440048828721 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06655936688184738 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.023359091952443123 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0021767301950603724 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007977967150509357 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014990291092544794 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003687522141262889 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035176024539396167 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015827175229787827 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030871517956256866 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0238583255559206 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008217009017243981 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030868660658597946 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029231635853648186 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02986077219247818 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009028848260641098 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005663419608026743 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01862442120909691 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018641871865838766 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029878368601202965 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011889907531440258 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00029952527256682515 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.730793342692778e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008532543433830142 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004995380295440555 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015824193134903908 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016197044169530272 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0158045943826437 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018692875164560974 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003312093438580632 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003760245628654957 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002662800718098879 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.631591971497983e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03257304057478905 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001867986167781055 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010406015207991004 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003126797266304493 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006138619501143694 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028290768386796117 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007000764016993344 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0024382679257541895 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033064331859350204 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017569772899150848 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006723135011270642 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000923330313526094 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007537584169767797 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002862566849216819 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006645209155976772 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023575115483254194 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010195858776569366 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011449061334133148 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003718412946909666 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009402615949511528 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009530186653137207 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00273325527086854 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005106355994939804 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017605078173801303 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009550377726554871 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002905130386352539 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014903845265507698 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010970572009682655 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007110519800335169 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009654938476160169 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0052302624098956585 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00277356687001884 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038851459976285696 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.786481885181274e-06 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003305301652289927 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0062253521755337715 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00043727795127779245 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003556937153916806 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004283198621124029 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020344873890280724 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006863393937237561 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030144894495606422 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017909878864884377 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000151926651597023 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02356758899986744 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03680755943059921 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013807842042297125 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006258189678192139 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012958105653524399 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001710868236841634 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008012671605683863 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038126041181385517 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018337100045755506 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002458445494994521 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001075870473869145 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030787300784140825 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009141762857325375 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020655285567045212 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007831300608813763 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0020377887412905693 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.384058385971002e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001779669662937522 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006298309308476746 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041232953662984073 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015025405213236809 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0038357432931661606 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017859081272035837 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023432669695466757 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009853295050561428 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002220834605395794 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00048749707639217377 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01733827404677868 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005968841258436441 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009465053677558899 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015944847837090492 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006749017629772425 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007877301424741745 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007914872840046883 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02378665655851364 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0063618761487305164 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03102896362543106 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017984570004045963 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015181738417595625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005498213227838278 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017995029920712113 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001345784985460341 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0019352298695594072 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027697994373738766 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004250838537700474 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01964329183101654 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005067137070000172 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001887925318442285 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00777244009077549 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.06885101646184921 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00039617682341486216 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022903434932231903 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013508607633411884 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004301761800888926 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.036179594695568085 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001223267987370491 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024838609620928764 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035608941689133644 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02965601719915867 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001029670238494873 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004034401790704578 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011805862188339233 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.434927051188424e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006700546946376562 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0058604758232831955 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008042841218411922 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022570518776774406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005754308658652008 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.037490759044885635 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005187555798329413 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017412096494808793 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011191406520083547 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002876872895285487 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005298583302646875 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00599723681807518 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005045824218541384 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01400363352149725 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00708241481333971 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005940980627201498 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0037608242128044367 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012486549094319344 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017649408255238086 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008990839123725891 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002308862516656518 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00043697800720110536 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0036043731961399317 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022991711273789406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014925100549589843 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011082668788731098 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038182438584044576 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011126995086669922 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022179033840075135 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019633577903732657 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004224841017276049 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004872208461165428 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004074578173458576 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.334673814009875e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00200557429343462 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014688988449051976 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001608392922207713 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004810198151972145 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.474632441997528e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022328633349388838 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00236233021132648 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00456647202372551 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006053562392480671 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013651175424456596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010789978841785342 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003642185765784234 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006334185600280762 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007351036183536053 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002334935124963522 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012761203106492758 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002470860257744789 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00024958772701211274 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014979223487898707 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012432225048542023 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002328248927369714 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002803464885801077 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002844209666363895 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003171317221131176 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030849778559058905 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004883544985204935 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021903666493017226 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004246475291438401 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006835733074694872 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003293091431260109 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003248576249461621 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003232197370380163 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018947730131912977 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.545253250398673e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008005925337783992 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03525476157665253 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020116398110985756 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030646059894934297 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011074826761614531 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004930198192596436 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003216454992070794 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.436628609662876e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00046125479275360703 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005360495415516198 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016580597730353475 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002158869756385684 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015431773848831654 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022581900702789426 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006101093604229391 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009153190068900585 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005089241894893348 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005951294442638755 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003289193147793412 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005247516091912985 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013768956705462188 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005698819644749165 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0053109885193407536 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016528154956176877 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012846219760831445 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.019498033449053764 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03449741378426552 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013682546559721231 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00048796660848893225 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038168526953086257 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007971841841936111 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0060801380313932896 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025080833584070206 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000160614334163256 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002658987941686064 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011036689393222332 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004364357329905033 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6002282538684085e-05 | lossAlign: 0
+2025-09-23 01:30:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0923274607630447e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006460995879024267 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.423073500627652e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.039480820298194885 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005193229764699936 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017335737124085426 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01291933748871088 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01137991901487112 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000110504130134359 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04159865900874138 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001483136205933988 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004162775818258524 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002707681618630886 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029026668053120375 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005617630202323198 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017870193347334862 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013786883209832013 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016717471182346344 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007280276040546596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004895192105323076 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010904243681579828 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011677053989842534 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0023798588663339615 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029552817344665527 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.030072275549173355 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008493822533637285 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026454576291143894 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003153883619233966 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033942508161999285 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002775697794277221 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0050497413612902164 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003889875952154398 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011472331825643778 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014602317241951823 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016955604776740074 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008589981123805046 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01623157039284706 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01360299251973629 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.154586713411845e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020141607150435448 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023031712044030428 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021994889539200813 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016900491900742054 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002617682097479701 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00218134350143373 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029096179641783237 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013617713702842593 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00036359793739393353 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025255737826228142 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026332633569836617 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004764685407280922 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00048491574125364423 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018511205911636353 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006973851122893393 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001611471176147461 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002188442158512771 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00036312444717623293 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017452076077461243 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012683370150625706 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007577314390800893 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012476436793804169 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005642800242640078 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032451076549477875 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00796746090054512 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033577851951122284 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013878558529540896 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001618376700207591 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005268733948469162 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008549499325454235 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0019331190269440413 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0059892176650464535 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004593209829181433 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005914220819249749 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012093055556761101 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005779532715678215 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016202544793486595 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008314741426147521 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010716094635426998 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000251010904321447 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010232862085103989 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002585425041615963 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00242854212410748 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.554840077413246e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0019150603329762816 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005771255237050354 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02617080695927143 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012702473439276218 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015927630010992289 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02496274933218956 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01903102546930313 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031858673319220543 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005038255476392806 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017416900023818016 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004869798664003611 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014658834785223007 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005683803930878639 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012593565043061972 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00867206510156393 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004152609501034021 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003977564629167318 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038166006561368704 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030986557248979807 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017492915503680706 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.089972496032715e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023850146681070328 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00069217145210132 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002996804192662239 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007947738282382488 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019626998982857913 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009560168837197125 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014350890705827624 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022248532623052597 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016824858030304313 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0033832050394266844 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005138441920280457 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.031762462109327316 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0021648970432579517 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016123931854963303 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013385878992266953 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004721457662526518 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011405019322410226 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015890926588326693 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001080506481230259 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001284897793084383 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029470939189195633 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.00659875292331e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002782701514661312 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003123090718872845 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0028120819479227066 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006397037650458515 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008966978639364243 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00581086752936244 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018963413313031197 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002484308322891593 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001414611586369574 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017276598373427987 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.312985013006255e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010271868668496609 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009869461646303535 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005039466195739806 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.020467620342969894 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00105965044349432 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00168736488558352 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001388845848850906 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.535676170140505e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004709262866526842 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001318175927735865 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001411879202350974 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003478565951809287 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003687951248139143 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005326051614247262 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.710329034831375e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012693253811448812 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005738101899623871 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013340298319235444 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001926584227476269 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.041384462267160416 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010603971313685179 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.5052300518145785e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015466139651834965 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008977299556136131 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010059485211968422 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006032189354300499 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006478928844444454 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000646713247988373 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021190207917243242 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.050532126915641e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01417078822851181 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007029940607026219 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003396100946702063 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4083364880643785e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003846823237836361 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013978754577692598 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016604291158728302 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010364532499806955 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013415870489552617 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025579947978258133 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000662985781673342 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003532200353220105 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006451306398957968 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002024023560807109 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013546244008466601 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035939563531428576 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005124502349644899 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006534317508339882 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0024900285061448812 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007684696465730667 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0093447370454669 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002652228286024183 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016735154204070568 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.284206756390631e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009055470582097769 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003488050540909171 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013087099068798125 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018449564231559634 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008982713334262371 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011507290415465832 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6895122826099396e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006845146417617798 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005610351799987257 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023787925601936877 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003864821628667414 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003147355280816555 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008199297823011875 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007063582306727767 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000881723128259182 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01147744432091713 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005763201625086367 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018016589456237853 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016548845451325178 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005646876059472561 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015562610933557153 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008841355447657406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00024482389562763274 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006248792633414268 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002465527504682541 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003542026737704873 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015419973991811275 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013053369475528598 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017380656208842993 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002811241429299116 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023288889497052878 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00034770392812788486 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0023299313616007566 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004840159963350743 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016523183148819953 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021613990247715265 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003720515174791217 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015235334285534918 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004474544897675514 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0052815768867731094 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008603949681855738 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004696884425356984 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003289045300334692 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01639782078564167 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001312092412263155 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009213234297931194 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007237810641527176 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0032683564350008965 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003829706402029842 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007428631070069969 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010441598715260625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00047989783342927694 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017441549571231008 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.322166442871094e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016435328871011734 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012690027942880988 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003487978538032621 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.63666573422961e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029094102792441845 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033004652708768845 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003422198351472616 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01883375085890293 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002790881844703108 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009136613225564361 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026642796001397073 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020775943994522095 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001272254972718656 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.133882586960681e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014331245329231024 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002368899527937174 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005205907509662211 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038231181679293513 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.021517077460885048 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.013026122003793716 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005600610747933388 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004571743484120816 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022432859987020493 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012454414973035455 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5116506801859941e-05 | lossAlign: 0
+2025-09-23 01:39:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.255477011203766e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001599213108420372 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5513581931591034e-05 | lossAlign: 0
+2025-09-23 01:39:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002839607885107398 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002257069805637002 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030507182236760855 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.05572190135717392 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.551082358579151e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014339417684823275 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017054521013051271 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016685103764757514 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00044570828322321177 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033367436844855547 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011963544238824397 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00311970803886652 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005711411940865219 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009309319779276848 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010580670787021518 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7153015253134072e-05 | lossAlign: 0
+2025-09-23 01:40:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.098735421895981e-05 | lossAlign: 0
+2025-09-23 01:40:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026559417601674795 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009721611277200282 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006575075094588101 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003021090233232826 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002756306203082204 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020657239656429738 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007127309218049049 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.393676787614822e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001723041496006772 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015644622966647148 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0039065214805305 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013296377437654883 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01863308995962143 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011535263620316982 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000590858981013298 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000826215953566134 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.929576531751081e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041227019391953945 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004209608305245638 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.009573113871738e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00042448550811968744 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006008863565512002 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027209650725126266 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005304126534610987 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004385919775813818 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.812549716210924e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020659063011407852 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005401553935371339 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005756829399615526 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008244438213296235 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002538955770432949 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029124522116035223 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013092183507978916 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.318092346191406e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.858872413635254e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023165825405158103 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007329576648771763 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009166645468212664 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003506555513013154 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005876421928405762 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007063719443976879 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018993007019162178 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006224285461939871 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017409760039299726 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7639220459386706e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006239301292225718 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011633513495326042 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022354605607688427 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010256469249725342 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021224681404419243 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034058638848364353 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010169899323955178 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014409593131858855 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004040182684548199 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000266076996922493 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009836285607889295 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003868022176902741 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.625869794632308e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003246651031076908 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0056923869997262955 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.033635951578617096 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008091682684607804 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002578254498075694 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.398498514201492e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005747676827013493 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002921396808233112 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00025568564888089895 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003094377461820841 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00080130371497944 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002566735493019223 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.901764183770865e-05 | lossAlign: 0
+2025-09-23 01:42:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.038093538838439e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00047018678742460907 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017292629927396774 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1873821676999796e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019964270177297294 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.135617877589539e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014020795933902264 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004248814657330513 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010429968097014353 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00040406660991720855 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005036830902099609 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010323231108486652 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026983989402651787 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005305652506649494 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006962910410948098 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.7990655730245635e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010225602454738691 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.564562186715193e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031206131097860634 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026042081299237907 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014848595019429922 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004251830105204135 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007053613662719727 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000502163777127862 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029431467410176992 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001831944566220045 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006040586158633232 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008554093074053526 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019220667309127748 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00044099168735556304 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.616405178443529e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008303206413984299 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013112048618495464 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4729615941178054e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01576310582458973 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6596048226347193e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033335472107864916 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.7263721828348935e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01073481049388647 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.34424141026102e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.022290950641036034 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0036047508474439383 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02071239799261093 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018480988219380379 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001573044719407335 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006431125570088625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032755875145085156 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.855327178025618e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015033756790217012 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001982285175472498 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011320017511025071 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.3647905588150024e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009513985714875162 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004470750689506531 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018493121024221182 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014441381790675223 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.38117630337365e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.09919121011626e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012308751232922077 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.541586481034756e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.7542252256535e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.53970348846633e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013394769048318267 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006618215702474117 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041681856964714825 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003557687741704285 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007729940116405487 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001019481715047732 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017057187505997717 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000999582465738058 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015294695040211082 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00578272994607687 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003151865385007113 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.0750044465530664e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000513755134306848 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.683819760335609e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012872570368926972 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002850765304174274 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015331745089497417 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00037977052852511406 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001612742053112015 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026494422927498817 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00037253566551953554 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.623232573270798e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.80278244544752e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02111407369375229 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022937393805477768 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018113024532794952 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04295611009001732 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.413768616970628e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023913479526527226 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035646153264679015 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017393475398421288 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004547332413494587 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0019590489100664854 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017241766909137368 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004089067690074444 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013539809733629227 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00080772367073223 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004889864358119667 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.968576366896741e-06 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005324577796272933 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002341457176953554 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008903288282454014 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002642428735271096 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010067401453852654 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006553199142217636 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.019677933480125e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011100980191258714 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.026629773899912834 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018890952924266458 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022070623526815325 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015909946523606777 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002858756110072136 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002020902611548081 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006123464088886976 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.968323289882392e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.67314787581563e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018074888736009598 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004553094622679055 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003345845325384289 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004382027836982161 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011746278032660484 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.912802488543093e-05 | lossAlign: 0
+2025-09-23 01:45:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005929703824222088 | lossAlign: 0
+2025-09-23 01:46:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007900211028754711 | lossAlign: 0
+2025-09-23 01:46:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000341020873747766 | lossAlign: 0
+2025-09-23 01:46:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012876037508249283 | lossAlign: 0
+2025-09-23 01:46:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00024110698723234236 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001268115360289812 | lossAlign: 0
+2025-09-23 01:46:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0021597594022750854 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015421127318404615 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0036281694192439318 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015385229198727757 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004193305969238281 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.02149541676044464 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009994457941502333 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008965459419414401 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009608749533072114 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0453619621694088 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009795802179723978 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027363139670342207 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008968387730419636 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013577465142589062 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023279114975593984 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010084233508678153 | lossAlign: 0
+2025-09-23 01:46:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4181797673227265e-05 | lossAlign: 0
+2025-09-23 01:46:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.399835547199473e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023685731866862625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011667641811072826 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021833689243067056 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009050539694726467 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007170627824962139 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005126771866343915 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011446347460150719 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003565076913218945 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002947747241705656 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007783112116158009 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018329849699512124 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002178173279389739 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008622714318335056 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.596730625256896e-05 | lossAlign: 0
+2025-09-23 01:47:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0020940632093697786 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003034683410078287 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016637740191072226 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.915617268532515e-05 | lossAlign: 0
+2025-09-23 01:47:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002001889981329441 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002717037277761847 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00042661032057367265 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.972289702389389e-05 | lossAlign: 0
+2025-09-23 01:47:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013817519356962293 | lossAlign: 0
+2025-09-23 01:47:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016622280236333609 | lossAlign: 0
+2025-09-23 01:47:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009831283241510391 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.927837886090856e-05 | lossAlign: 0
+2025-09-23 01:47:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009200198110193014 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00655124057084322 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001398000749759376 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008329966804012656 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.056144825881347e-05 | lossAlign: 0
+2025-09-23 01:47:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016705526504665613 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008377812919206917 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014027662109583616 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017822360678110272 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6258288926328532e-05 | lossAlign: 0
+2025-09-23 01:47:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011593010276556015 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.004363705054857e-05 | lossAlign: 0
+2025-09-23 01:47:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.293473805068061e-05 | lossAlign: 0
+2025-09-23 01:47:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.8252844862872735e-05 | lossAlign: 0
+2025-09-23 01:47:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.704376523382962e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00045323645463213325 | lossAlign: 0
+2025-09-23 01:47:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2439226086135022e-05 | lossAlign: 0
+2025-09-23 01:47:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016004177741706371 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00027405921719036996 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.910845645004883e-05 | lossAlign: 0
+2025-09-23 01:48:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011543396394699812 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00042457928066141903 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.8018071791157126e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.038464177399873734 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017029866576194763 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00037360473652370274 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.082040711888112e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00044680325663648546 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023273006081581116 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017362041398882866 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013147114077582955 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025818159338086843 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004431703127920628 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012974071432836354 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.652398198843002e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8885840947623365e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017522602865938097 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0023827580735087395 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00463319756090641 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002915220393333584 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002448577724862844 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010872800834476948 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001412038691341877 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004275667481124401 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.29607675364241e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012904309551231563 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012498674914240837 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0034378748387098312 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.912968481425196e-05 | lossAlign: 0
+2025-09-23 01:48:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008305007591843605 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003910770465154201 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018706604605540633 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005956904496997595 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007207485847175121 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.32394978008233e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003763996995985508 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003164311172440648 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015824948204681277 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012060421518981457 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009388721664436162 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011496064253151417 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01304896455258131 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.016895637614653e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031415338162332773 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008083662949502468 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008724378421902657 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004120603553019464 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031872341060079634 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004697621916420758 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6285648345947266e-05 | lossAlign: 0
+2025-09-23 01:49:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018047284102067351 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015742246061563492 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009000235004350543 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011111710919067264 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002027980808634311 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.105534703237936e-05 | lossAlign: 0
+2025-09-23 01:49:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017817752668634057 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015949162479955703 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.028304722160100937 | lossAlign: 0
+2025-09-23 01:49:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.0994477684726e-06 | lossAlign: 0
+2025-09-23 01:49:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022731255739927292 | lossAlign: 0
+2025-09-23 01:49:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.852686733007431e-05 | lossAlign: 0
+2025-09-23 01:49:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009827329777181149 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.952388917445205e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032684041070751846 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007345676422119141 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013988714199513197 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020395871251821518 | lossAlign: 0
+2025-09-23 01:50:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8149856259697117e-05 | lossAlign: 0
+2025-09-23 01:50:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.318328764289618e-05 | lossAlign: 0
+2025-09-23 01:50:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.362855522937025e-06 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007293929811567068 | lossAlign: 0
+2025-09-23 01:50:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.424607949564233e-05 | lossAlign: 0
+2025-09-23 01:50:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001202123356051743 | lossAlign: 0
+2025-09-23 01:50:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013784084003418684 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010658634710125625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033606842043809593 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003466000489424914 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008585168980062008 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011098672985099256 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018285935220774263 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.795302058686502e-05 | lossAlign: 0
+2025-09-23 01:50:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.515349453664385e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.2586325434967875e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024772828444838524 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5413930416107178e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002224380150437355 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016875324945431203 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.299730011960492e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029139339458197355 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.156355761457235e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.018893057480454445 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0032887551933526993 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.493476858944632e-05 | lossAlign: 0
+2025-09-23 01:50:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.7559522247174755e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035792781272903085 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.029396185651421547 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004272941499948502 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01184438169002533 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005658170557580888 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008466309518553317 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004992811009287834 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006128145614638925 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003210249706171453 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004674221388995647 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4364690034417436e-05 | lossAlign: 0
+2025-09-23 01:51:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008067831513471901 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00648437300696969 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.03706682473421097 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015432862564921379 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006905891350470483 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005084109725430608 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0026305168867111206 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004155940376222134 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0021114677656441927 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002857812913134694 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0045325555838644505 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012263751705177128 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007095803506672382 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001069679157808423 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4827515517245047e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002124255057424307 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004237559041939676 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017615174874663353 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022294172958936542 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015105018392205238 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014175320393405855 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003874378162436187 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005890689208172262 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033878497197292745 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.934413977432996e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001446771202608943 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.017031684517860413 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001146132592111826 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010529698338359594 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.66191852663178e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011290532536804676 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015766252181492746 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.963273674249649e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9229228200856596e-05 | lossAlign: 0
+2025-09-23 01:52:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.179960034089163e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.009025813080370426 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006836479878984392 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010720763384597376 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004235244821757078 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027213154826313257 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020752177806571126 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022781365260016173 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4262655390193686e-05 | lossAlign: 0
+2025-09-23 01:52:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.615255890414119e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.99880955228582e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009370478801429272 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001848926767706871 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00045102450530976057 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022403716866392642 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003149871772620827 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022716392413713038 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013849258539266884 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014150993956718594 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.953458796488121e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002145241596736014 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.940690971328877e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.532600385369733e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016737623373046517 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.283158366684802e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013154979387763888 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010739583522081375 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013735255924984813 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4872551219013985e-05 | lossAlign: 0
+2025-09-23 01:52:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.401166607858613e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.800639286870137e-05 | lossAlign: 0
+2025-09-23 01:53:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008394773118197918 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009150833357125521 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.9302714362274855e-05 | lossAlign: 0
+2025-09-23 01:53:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7264257116476074e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.007229621056467295 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014965779148042202 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.428172931307927e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04851879924535751 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00199150200933218 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00039535522228106856 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009571266127750278 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0035803336650133133 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5942319805617444e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002532853977754712 | lossAlign: 0
+2025-09-23 01:53:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.694923336501233e-05 | lossAlign: 0
+2025-09-23 01:53:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001917972113005817 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00034632510505616665 | lossAlign: 0
+2025-09-23 01:53:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016742147272452712 | lossAlign: 0
+2025-09-23 01:53:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.362302934168838e-05 | lossAlign: 0
+2025-09-23 01:53:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.983427349245176e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003224793588742614 | lossAlign: 0
+2025-09-23 01:53:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.679309520521201e-05 | lossAlign: 0
+2025-09-23 01:53:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008362540975213051 | lossAlign: 0
+2025-09-23 01:53:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.015897544100880623 | lossAlign: 0
+2025-09-23 01:53:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005746789742261171 | lossAlign: 0
+2025-09-23 01:53:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.321876753645483e-06 | lossAlign: 0
+2025-09-23 01:53:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0020847388077527285 | lossAlign: 0
+2025-09-23 01:53:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011375688336556777 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004278844688087702 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018991396063938737 | lossAlign: 0
+2025-09-23 01:53:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009666642872616649 | lossAlign: 0
+2025-09-23 01:53:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017534733342472464 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3379921913146973e-05 | lossAlign: 0
+2025-09-23 01:54:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009608720429241657 | lossAlign: 0
+2025-09-23 01:54:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04762702062726021 | lossAlign: 0
+2025-09-23 01:54:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.190898860339075e-05 | lossAlign: 0
+2025-09-23 01:54:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003774308832362294 | lossAlign: 0
+2025-09-23 01:54:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.010474652983248234 | lossAlign: 0
+2025-09-23 01:54:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012759502278640866 | lossAlign: 0
+2025-09-23 01:54:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00027204310754314065 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027407696470618248 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005251903785392642 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002663307241164148 | lossAlign: 0
+2025-09-23 01:54:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027958182618021965 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025364516768604517 | lossAlign: 0
+2025-09-23 01:54:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3675329430261627e-05 | lossAlign: 0
+2025-09-23 01:54:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030202619382180274 | lossAlign: 0
+2025-09-23 01:54:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001480604405514896 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005796228069812059 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006522102630697191 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017981692217290401 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002860462758690119 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035541682154871523 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011545810411917046 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011695296416291967 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005594940157607198 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002762253163382411 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001072912200470455 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001113741600420326 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028050877153873444 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.323741349158809e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013494195882230997 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021929029026068747 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007845107465982437 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002367920009419322 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006086397334001958 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017186648910865188 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006883768946863711 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004697928670793772 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016763432649895549 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.074202686548233e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005705133080482483 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002705511578824371 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.04094851389527321 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003618371207267046 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006205589510500431 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015993239358067513 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010441314952913672 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003617022419348359 | lossAlign: 0
+2025-09-23 01:55:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.740047370432876e-05 | lossAlign: 0
+2025-09-23 01:55:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.82200659159571e-05 | lossAlign: 0
+2025-09-23 01:55:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007276267861016095 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00036206841468811035 | lossAlign: 0
+2025-09-23 01:55:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.624163067201152e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.024014554917812347 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016247456369455904 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015941454330459237 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005022342666052282 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.0072758060414344e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018535597482696176 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000691251247189939 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007400146569125354 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007239296101033688 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.634781362256035e-05 | lossAlign: 0
+2025-09-23 01:55:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006701535079628229 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005073314532637596 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.049581755476538e-05 | lossAlign: 0
+2025-09-23 01:55:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013160563539713621 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005464646033942699 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.047861486673355e-05 | lossAlign: 0
+2025-09-23 01:56:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0653983736119699e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.012189415283501148 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016916560707613826 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023891353339422494 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7355358068016358e-05 | lossAlign: 0
+2025-09-23 01:56:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006150949629954994 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016732235671952367 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.014801345765590668 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001103025395423174 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013233814388513565 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0038631202187389135 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.542133243987337e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.045001499354839325 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026890472508966923 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.0301256376551464e-05 | lossAlign: 0
+2025-09-23 01:56:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022558097261935472 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011773336154874414 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012833424843847752 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.016745518893003464 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014653205289505422 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003099346940871328 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000479582668049261 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010178408410865813 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.469394843908958e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00033414841163903475 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012694380711764097 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009361328557133675 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00027438229881227016 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019752886146306992 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002601811196655035 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008125351741909981 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015203571820165962 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008333930745720863 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1052937881904654e-05 | lossAlign: 0
+2025-09-23 01:56:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001323290343862027 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031584789394401014 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010256785753881559 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.63599169254303e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016675014921929687 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005544601008296013 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.0416878366377205e-05 | lossAlign: 0
+2025-09-23 01:57:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.688904356153216e-06 | lossAlign: 0
+2025-09-23 01:57:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5269508114433847e-05 | lossAlign: 0
+2025-09-23 01:57:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004810962709598243 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004017743922304362 | lossAlign: 0
+2025-09-23 01:57:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008191960863769054 | lossAlign: 0
+2025-09-23 01:57:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0837784177274443e-05 | lossAlign: 0
+2025-09-23 01:57:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.95651074743364e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010312660742783919 | lossAlign: 0
+2025-09-23 01:57:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.173488797387108e-05 | lossAlign: 0
+2025-09-23 01:57:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008553923689760268 | lossAlign: 0
+2025-09-23 01:57:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028361781733110547 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009250203729607165 | lossAlign: 0
+2025-09-23 01:57:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.045857975957915e-05 | lossAlign: 0
+2025-09-23 01:57:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002119209966622293 | lossAlign: 0
+2025-09-23 01:57:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.865613926900551e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011420249938964844 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012908817734569311 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013807296636514366 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000123369405628182 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.244139199727215e-05 | lossAlign: 0
+2025-09-23 01:57:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005967986071482301 | lossAlign: 0
+2025-09-23 01:57:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.3129690564237535e-05 | lossAlign: 0
+2025-09-23 01:57:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.653547850670293e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1217361791059375e-05 | lossAlign: 0
+2025-09-23 01:57:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002813329338096082 | lossAlign: 0
+2025-09-23 01:57:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.672379772178829e-05 | lossAlign: 0
+2025-09-23 01:57:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004723291494883597 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006772946217097342 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002274373546242714 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009336537914350629 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002995436079800129 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002056014200206846 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002985048049595207 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003613448643591255 | lossAlign: 0
+2025-09-23 01:58:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.381225830409676e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.757909381529316e-05 | lossAlign: 0
+2025-09-23 01:58:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.158478648401797e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1405301847844385e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00027223301003687084 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014591505168937147 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007253730436787009 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006560284527949989 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001832092966651544 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014654051046818495 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005129575729370117 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.981159119983204e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028964190278202295 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01109849102795124 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00024765351554378867 | lossAlign: 0
+2025-09-23 01:58:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.904504981415812e-05 | lossAlign: 0
+2025-09-23 01:58:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7420059268479235e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016218666860368103 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002151519525796175 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017613229574635625 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016054368461482227 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012205913662910461 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00036587269278243184 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023582976427860558 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00043408042984083295 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002815475454553962 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022833133698441088 | lossAlign: 0
+2025-09-23 01:58:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.851745754625881e-06 | lossAlign: 0
+2025-09-23 01:58:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003977761953137815 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025330332573503256 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005061300005763769 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.118244760320522e-05 | lossAlign: 0
+2025-09-23 01:59:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.5112381738144904e-05 | lossAlign: 0
+2025-09-23 01:59:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003849627391900867 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002706951927393675 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002161358279408887 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003714847844094038 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1442169125075452e-05 | lossAlign: 0
+2025-09-23 01:59:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012792983034159988 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012165028601884842 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006992191541939974 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.697947977343574e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.011299874633550644 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.729511288634967e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030360050732269883 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.954855467076413e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.118054782040417e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000575721263885498 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016481576312799007 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.391787661006674e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.721207031048834e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00029902439564466476 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014991569332778454 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007987071294337511 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010332530364394188 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.308555748546496e-05 | lossAlign: 0
+2025-09-23 01:59:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006700182566419244 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0024209003895521164 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007446412928402424 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004244162992108613 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017026234127115458 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015328233712352812 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.193247387884185e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.2196121537708677e-06 | lossAlign: 0
+2025-09-23 02:00:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012324543204158545 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031481904443353415 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020130474877078086 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0162811526679434e-05 | lossAlign: 0
+2025-09-23 02:00:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.788074824726209e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.843815157888457e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003800863341894001 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011552403448149562 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004872025456279516 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005836706259287894 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00036157690919935703 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.9555448387982324e-05 | lossAlign: 0
+2025-09-23 02:00:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014665145426988602 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011338591575622559 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014260036405175924 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.4784486565040424e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010659535182639956 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5994695786503144e-05 | lossAlign: 0
+2025-09-23 02:00:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.722589462995529e-05 | lossAlign: 0
+2025-09-23 02:00:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005310385604389012 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.925591489765793e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007150525925680995 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6707033864804544e-05 | lossAlign: 0
+2025-09-23 02:00:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0023028042633086443 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012722131214104593 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003208527632523328 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.29055717177107e-06 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000123598103527911 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0038061821833252907 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9714334232266992e-05 | lossAlign: 0
+2025-09-23 02:00:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004905909299850464 | lossAlign: 0
+2025-09-23 02:00:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007104123942553997 | lossAlign: 0
+2025-09-23 02:00:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.552785584470257e-05 | lossAlign: 0
+2025-09-23 02:01:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012392248027026653 | lossAlign: 0
+2025-09-23 02:01:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001238121883943677 | lossAlign: 0
+2025-09-23 02:01:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000620041333604604 | lossAlign: 0
+2025-09-23 02:01:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.613655568799004e-05 | lossAlign: 0
+2025-09-23 02:01:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.79966402053833e-05 | lossAlign: 0
+2025-09-23 02:01:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.435453542508185e-05 | lossAlign: 0
+2025-09-23 02:01:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.695484237046912e-05 | lossAlign: 0
+2025-09-23 02:01:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.424241003813222e-05 | lossAlign: 0
+2025-09-23 02:01:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.693576480960473e-05 | lossAlign: 0
+2025-09-23 02:01:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0028266790322959423 | lossAlign: 0
+2025-09-23 02:01:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009951849933713675 | lossAlign: 0
+2025-09-23 02:01:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005185026675462723 | lossAlign: 0
+2025-09-23 02:01:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002006926224566996 | lossAlign: 0
+2025-09-23 02:01:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001146255963249132 | lossAlign: 0
+2025-09-23 02:01:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020312974811531603 | lossAlign: 0
+2025-09-23 02:01:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0019029827089980245 | lossAlign: 0
+2025-09-23 02:01:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.2277056965976954e-05 | lossAlign: 0
+2025-09-23 02:01:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002469930041115731 | lossAlign: 0
+2025-09-23 02:01:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.942150063579902e-05 | lossAlign: 0
+2025-09-23 02:01:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.037906597252004e-05 | lossAlign: 0
+2025-09-23 02:01:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8176131561631337e-05 | lossAlign: 0
+2025-09-23 02:01:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.668045221478678e-05 | lossAlign: 0
+2025-09-23 02:01:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005341304931789637 | lossAlign: 0
+2025-09-23 02:01:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008662967593409121 | lossAlign: 0
+2025-09-23 02:01:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.238037894945592e-05 | lossAlign: 0
+2025-09-23 02:01:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00027664785739034414 | lossAlign: 0
+2025-09-23 02:01:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0024770733434706926 | lossAlign: 0
+2025-09-23 02:01:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005364523967728019 | lossAlign: 0
+2025-09-23 02:01:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003495023993309587 | lossAlign: 0
+2025-09-23 02:01:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012876589607913047 | lossAlign: 0
+2025-09-23 02:01:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.183719960972667e-05 | lossAlign: 0
+2025-09-23 02:01:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.36112633603625e-05 | lossAlign: 0
+2025-09-23 02:02:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012524666090030223 | lossAlign: 0
+2025-09-23 02:02:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015907700872048736 | lossAlign: 0
+2025-09-23 02:02:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.421402652747929e-05 | lossAlign: 0
+2025-09-23 02:02:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000908682297449559 | lossAlign: 0
+2025-09-23 02:02:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006900306907482445 | lossAlign: 0
+2025-09-23 02:02:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019128932035528123 | lossAlign: 0
+2025-09-23 02:02:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006196270114742219 | lossAlign: 0
+2025-09-23 02:02:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014769943663850427 | lossAlign: 0
+2025-09-23 02:02:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009325377177447081 | lossAlign: 0
+2025-09-23 02:02:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005085375159978867 | lossAlign: 0
+2025-09-23 02:02:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.700738256564364e-05 | lossAlign: 0
+2025-09-23 02:02:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.67605083133094e-05 | lossAlign: 0
+2025-09-23 02:02:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00025406989152543247 | lossAlign: 0
+2025-09-23 02:02:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002971784269902855 | lossAlign: 0
+2025-09-23 02:02:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014811281289439648 | lossAlign: 0
+2025-09-23 02:02:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.231304284185171e-05 | lossAlign: 0
+2025-09-23 02:02:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005623456090688705 | lossAlign: 0
+2025-09-23 02:02:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011202239693375304 | lossAlign: 0
+2025-09-23 02:02:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028215095517225564 | lossAlign: 0
+2025-09-23 02:02:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008881356916390359 | lossAlign: 0
+2025-09-23 02:02:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.285217462689616e-05 | lossAlign: 0
+2025-09-23 02:02:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8072357963537797e-05 | lossAlign: 0
+2025-09-23 02:02:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006561033078469336 | lossAlign: 0
+2025-09-23 02:02:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.283119884959888e-06 | lossAlign: 0
+2025-09-23 02:02:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011954880028497428 | lossAlign: 0
+2025-09-23 02:02:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001686726900516078 | lossAlign: 0
+2025-09-23 02:02:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4129638657323085e-05 | lossAlign: 0
+2025-09-23 02:02:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025021176785230637 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7590849640546367e-05 | lossAlign: 0
+2025-09-23 02:02:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005411178572103381 | lossAlign: 0
+2025-09-23 02:02:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.125263199559413e-05 | lossAlign: 0
+2025-09-23 02:02:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.111867358209565e-05 | lossAlign: 0
+2025-09-23 02:03:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.176299499813467e-05 | lossAlign: 0
+2025-09-23 02:03:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028819325962103903 | lossAlign: 0
+2025-09-23 02:03:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00025360548170283437 | lossAlign: 0
+2025-09-23 02:03:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.278488141717389e-05 | lossAlign: 0
+2025-09-23 02:03:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00036810990422964096 | lossAlign: 0
+2025-09-23 02:03:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.6096825978311244e-06 | lossAlign: 0
+2025-09-23 02:03:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.316899766214192e-05 | lossAlign: 0
+2025-09-23 02:03:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008465934079140425 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001022863361868076 | lossAlign: 0
+2025-09-23 02:03:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017086323350667953 | lossAlign: 0
+2025-09-23 02:03:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3969247447676025e-05 | lossAlign: 0
+2025-09-23 02:03:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.8626814532326534e-05 | lossAlign: 0
+2025-09-23 02:03:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.419831722974777e-05 | lossAlign: 0
+2025-09-23 02:03:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.7511861086823046e-05 | lossAlign: 0
+2025-09-23 02:03:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003869319101795554 | lossAlign: 0
+2025-09-23 02:03:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.911200110451318e-06 | lossAlign: 0
+2025-09-23 02:03:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007907899562269449 | lossAlign: 0
+2025-09-23 02:03:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017228068318217993 | lossAlign: 0
+2025-09-23 02:03:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017269073578063399 | lossAlign: 0
+2025-09-23 02:03:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007505114190280437 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008368648705072701 | lossAlign: 0
+2025-09-23 02:03:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.038202521565836e-05 | lossAlign: 0
+2025-09-23 02:03:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.958617061376572e-05 | lossAlign: 0
+2025-09-23 02:03:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021261264919303358 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018208273104391992 | lossAlign: 0
+2025-09-23 02:03:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004750862717628479 | lossAlign: 0
+2025-09-23 02:03:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.145346585777588e-05 | lossAlign: 0
+2025-09-23 02:03:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.833306775253732e-06 | lossAlign: 0
+2025-09-23 02:03:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003537260228767991 | lossAlign: 0
+2025-09-23 02:03:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.284704224730376e-06 | lossAlign: 0
+2025-09-23 02:03:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.415882671717554e-05 | lossAlign: 0
+2025-09-23 02:03:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.0413898861734197e-05 | lossAlign: 0
+2025-09-23 02:03:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.771188342710957e-05 | lossAlign: 0
+2025-09-23 02:03:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001785364147508517 | lossAlign: 0
+2025-09-23 02:03:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0024459182750433683 | lossAlign: 0
+2025-09-23 02:03:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.8692473026458174e-05 | lossAlign: 0
+2025-09-23 02:04:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015285747358575463 | lossAlign: 0
+2025-09-23 02:04:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.372799033561023e-05 | lossAlign: 0
+2025-09-23 02:04:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002861088141798973 | lossAlign: 0
+2025-09-23 02:04:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6982637791661546e-05 | lossAlign: 0
+2025-09-23 02:04:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011182994057890028 | lossAlign: 0
+2025-09-23 02:04:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.282147710910067e-05 | lossAlign: 0
+2025-09-23 02:04:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016413677076343447 | lossAlign: 0
+2025-09-23 02:04:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.050193719100207e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.462563497829251e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00042413806659169495 | lossAlign: 0
+2025-09-23 02:04:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022339734714478254 | lossAlign: 0
+2025-09-23 02:04:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012003257870674133 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006240654620341957 | lossAlign: 0
+2025-09-23 02:04:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035331270191818476 | lossAlign: 0
+2025-09-23 02:04:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003072762629017234 | lossAlign: 0
+2025-09-23 02:04:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001720994187053293 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4369239326915704e-05 | lossAlign: 0
+2025-09-23 02:04:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.423542360309511e-05 | lossAlign: 0
+2025-09-23 02:04:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032224919414147735 | lossAlign: 0
+2025-09-23 02:04:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005176668055355549 | lossAlign: 0
+2025-09-23 02:04:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012956071877852082 | lossAlign: 0
+2025-09-23 02:04:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.531146335764788e-05 | lossAlign: 0
+2025-09-23 02:04:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.109235310854274e-06 | lossAlign: 0
+2025-09-23 02:04:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.337020517501514e-06 | lossAlign: 0
+2025-09-23 02:04:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004459978954400867 | lossAlign: 0
+2025-09-23 02:04:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004158496856689453 | lossAlign: 0
+2025-09-23 02:04:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005008894950151443 | lossAlign: 0
+2025-09-23 02:04:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.395668944809586e-05 | lossAlign: 0
+2025-09-23 02:04:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041208710172213614 | lossAlign: 0
+2025-09-23 02:04:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010728454799391329 | lossAlign: 0
+2025-09-23 02:04:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007239282131195068 | lossAlign: 0
+2025-09-23 02:04:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001314831170020625 | lossAlign: 0
+2025-09-23 02:05:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015933172835502774 | lossAlign: 0
+2025-09-23 02:05:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009582502534613013 | lossAlign: 0
+2025-09-23 02:05:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7450561901787296e-05 | lossAlign: 0
+2025-09-23 02:05:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038317902362905443 | lossAlign: 0
+2025-09-23 02:05:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00039897809620015323 | lossAlign: 0
+2025-09-23 02:05:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022500564227811992 | lossAlign: 0
+2025-09-23 02:05:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004243774455972016 | lossAlign: 0
+2025-09-23 02:05:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.807045191526413e-05 | lossAlign: 0
+2025-09-23 02:05:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.536523647402646e-06 | lossAlign: 0
+2025-09-23 02:05:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003866506740450859 | lossAlign: 0
+2025-09-23 02:05:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.6893954277038574e-05 | lossAlign: 0
+2025-09-23 02:05:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3151811799616553e-05 | lossAlign: 0
+2025-09-23 02:05:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007680351845920086 | lossAlign: 0
+2025-09-23 02:05:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.588004857301712e-05 | lossAlign: 0
+2025-09-23 02:05:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014922904665581882 | lossAlign: 0
+2025-09-23 02:05:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018033830565400422 | lossAlign: 0
+2025-09-23 02:05:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009485626360401511 | lossAlign: 0
+2025-09-23 02:05:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010326062329113483 | lossAlign: 0
+2025-09-23 02:05:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022480807092506438 | lossAlign: 0
+2025-09-23 02:05:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001160711282864213 | lossAlign: 0
+2025-09-23 02:05:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4322660212637857e-05 | lossAlign: 0
+2025-09-23 02:05:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2402762624551542e-05 | lossAlign: 0
+2025-09-23 02:05:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003934133565053344 | lossAlign: 0
+2025-09-23 02:05:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.791139170061797e-05 | lossAlign: 0
+2025-09-23 02:05:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0074638339574449e-05 | lossAlign: 0
+2025-09-23 02:05:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.64553328230977e-05 | lossAlign: 0
+2025-09-23 02:05:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001353330590063706 | lossAlign: 0
+2025-09-23 02:05:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002822713868226856 | lossAlign: 0
+2025-09-23 02:05:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.5055567170493305e-05 | lossAlign: 0
+2025-09-23 02:05:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.053867648210144e-06 | lossAlign: 0
+2025-09-23 02:05:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.589557647705078e-06 | lossAlign: 0
+2025-09-23 02:05:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003794295946136117 | lossAlign: 0
+2025-09-23 02:05:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013975208275951445 | lossAlign: 0
+2025-09-23 02:05:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031681612599641085 | lossAlign: 0
+2025-09-23 02:05:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.805141750490293e-05 | lossAlign: 0
+2025-09-23 02:05:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7888843507971615e-05 | lossAlign: 0
+2025-09-23 02:06:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.524309926840942e-06 | lossAlign: 0
+2025-09-23 02:06:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009937956929206848 | lossAlign: 0
+2025-09-23 02:06:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031999059137888253 | lossAlign: 0
+2025-09-23 02:06:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.915400783531368e-05 | lossAlign: 0
+2025-09-23 02:06:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.195672464556992e-05 | lossAlign: 0
+2025-09-23 02:06:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008435999043285847 | lossAlign: 0
+2025-09-23 02:06:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00034494532155804336 | lossAlign: 0
+2025-09-23 02:06:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7450332961743698e-05 | lossAlign: 0
+2025-09-23 02:06:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014540761185344309 | lossAlign: 0
+2025-09-23 02:06:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3652394954988267e-05 | lossAlign: 0
+2025-09-23 02:06:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001304215838899836 | lossAlign: 0
+2025-09-23 02:06:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6381263776565902e-05 | lossAlign: 0
+2025-09-23 02:06:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005338221089914441 | lossAlign: 0
+2025-09-23 02:06:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018317604553885758 | lossAlign: 0
+2025-09-23 02:06:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0029951136093586683 | lossAlign: 0
+2025-09-23 02:06:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.928779526380822e-05 | lossAlign: 0
+2025-09-23 02:06:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.347684681415558e-06 | lossAlign: 0
+2025-09-23 02:06:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.87271055742167e-05 | lossAlign: 0
+2025-09-23 02:06:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015599653124809265 | lossAlign: 0
+2025-09-23 02:06:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.3547643397469074e-05 | lossAlign: 0
+2025-09-23 02:06:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.805448406841606e-05 | lossAlign: 0
+2025-09-23 02:06:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015300540253520012 | lossAlign: 0
+2025-09-23 02:06:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7131310818949714e-05 | lossAlign: 0
+2025-09-23 02:06:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.2980595278786495e-05 | lossAlign: 0
+2025-09-23 02:06:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2537625480035786e-05 | lossAlign: 0
+2025-09-23 02:06:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.9370286685880274e-05 | lossAlign: 0
+2025-09-23 02:06:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014427562709897757 | lossAlign: 0
+2025-09-23 02:06:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.748199666617438e-05 | lossAlign: 0
+2025-09-23 02:06:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.797273378353566e-06 | lossAlign: 0
+2025-09-23 02:06:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014615058898925781 | lossAlign: 0
+2025-09-23 02:06:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.6451699492754415e-05 | lossAlign: 0
+2025-09-23 02:06:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017296976875513792 | lossAlign: 0
+2025-09-23 02:07:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032163411378860474 | lossAlign: 0
+2025-09-23 02:07:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.772216612356715e-05 | lossAlign: 0
+2025-09-23 02:07:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001496547629358247 | lossAlign: 0
+2025-09-23 02:07:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0038737591821700335 | lossAlign: 0
+2025-09-23 02:07:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.550956848310307e-05 | lossAlign: 0
+2025-09-23 02:07:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004989406443201005 | lossAlign: 0
+2025-09-23 02:07:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.028684871736914e-06 | lossAlign: 0
+2025-09-23 02:07:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6896246961550787e-05 | lossAlign: 0
+2025-09-23 02:07:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003997745516244322 | lossAlign: 0
+2025-09-23 02:07:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.621278316742973e-06 | lossAlign: 0
+2025-09-23 02:07:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.689466368290596e-05 | lossAlign: 0
+2025-09-23 02:07:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007161817629821599 | lossAlign: 0
+2025-09-23 02:07:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00047921849181875587 | lossAlign: 0
+2025-09-23 02:07:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.178080391488038e-05 | lossAlign: 0
+2025-09-23 02:07:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002053247590083629 | lossAlign: 0
+2025-09-23 02:07:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.194252925226465e-06 | lossAlign: 0
+2025-09-23 02:07:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013849331298843026 | lossAlign: 0
+2025-09-23 02:07:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5243271011277102e-05 | lossAlign: 0
+2025-09-23 02:07:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012280921509955078 | lossAlign: 0
+2025-09-23 02:07:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015769699530210346 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.635597285116091e-05 | lossAlign: 0
+2025-09-23 02:07:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015594626893289387 | lossAlign: 0
+2025-09-23 02:07:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.954650598345324e-05 | lossAlign: 0
+2025-09-23 02:07:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4343538573011756e-05 | lossAlign: 0
+2025-09-23 02:07:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010633656347636133 | lossAlign: 0
+2025-09-23 02:07:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.3636671509593725e-05 | lossAlign: 0
+2025-09-23 02:07:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.2066803618799895e-05 | lossAlign: 0
+2025-09-23 02:07:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.698990182485431e-05 | lossAlign: 0
+2025-09-23 02:07:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002908687456510961 | lossAlign: 0
+2025-09-23 02:07:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.0047688748454675e-05 | lossAlign: 0
+2025-09-23 02:07:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.899012416601181e-05 | lossAlign: 0
+2025-09-23 02:07:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.8757559852674603e-05 | lossAlign: 0
+2025-09-23 02:07:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.291942589887185e-05 | lossAlign: 0
+2025-09-23 02:07:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019091034482698888 | lossAlign: 0
+2025-09-23 02:07:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010581091919448227 | lossAlign: 0
+2025-09-23 02:07:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000355859607225284 | lossAlign: 0
+2025-09-23 02:08:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.568840712541714e-05 | lossAlign: 0
+2025-09-23 02:08:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.570510443751118e-06 | lossAlign: 0
+2025-09-23 02:08:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012422818690538406 | lossAlign: 0
+2025-09-23 02:08:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4588588783226442e-05 | lossAlign: 0
+2025-09-23 02:08:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.406442116713151e-05 | lossAlign: 0
+2025-09-23 02:08:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.76920038938988e-05 | lossAlign: 0
+2025-09-23 02:08:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1686630134354346e-05 | lossAlign: 0
+2025-09-23 02:08:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.01335946936160326 | lossAlign: 0
+2025-09-23 02:08:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2325784811982885e-05 | lossAlign: 0
+2025-09-23 02:08:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.545471362391254e-06 | lossAlign: 0
+2025-09-23 02:08:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.073951681173639e-06 | lossAlign: 0
+2025-09-23 02:08:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.14712519866589e-06 | lossAlign: 0
+2025-09-23 02:08:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019986099505331367 | lossAlign: 0
+2025-09-23 02:08:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.858896373771131e-05 | lossAlign: 0
+2025-09-23 02:08:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002817927743308246 | lossAlign: 0
+2025-09-23 02:08:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00028390545048750937 | lossAlign: 0
+2025-09-23 02:08:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016192055772989988 | lossAlign: 0
+2025-09-23 02:08:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.91959066898562e-05 | lossAlign: 0
+2025-09-23 02:08:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.116672299569473e-05 | lossAlign: 0
+2025-09-23 02:08:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3794553271727636e-05 | lossAlign: 0
+2025-09-23 02:08:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0991496057831682e-05 | lossAlign: 0
+2025-09-23 02:08:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.911140866985079e-06 | lossAlign: 0
+2025-09-23 02:08:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8889084458351135e-05 | lossAlign: 0
+2025-09-23 02:08:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0159615814918652e-05 | lossAlign: 0
+2025-09-23 02:08:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.5725533962249756e-05 | lossAlign: 0
+2025-09-23 02:08:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.8492431233171374e-05 | lossAlign: 0
+2025-09-23 02:08:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00047840154729783535 | lossAlign: 0
+2025-09-23 02:08:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.734812551352661e-05 | lossAlign: 0
+2025-09-23 02:08:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.800701208296232e-05 | lossAlign: 0
+2025-09-23 02:08:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7061478249379434e-05 | lossAlign: 0
+2025-09-23 02:08:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041208151378668845 | lossAlign: 0
+2025-09-23 02:08:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003316871589049697 | lossAlign: 0
+2025-09-23 02:09:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012018756387988105 | lossAlign: 0
+2025-09-23 02:09:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4693017647005036e-06 | lossAlign: 0
+2025-09-23 02:09:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.450479991646716e-06 | lossAlign: 0
+2025-09-23 02:09:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000345012842444703 | lossAlign: 0
+2025-09-23 02:09:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.542386058252305e-05 | lossAlign: 0
+2025-09-23 02:09:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7775642845663242e-05 | lossAlign: 0
+2025-09-23 02:09:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005901455879211426 | lossAlign: 0
+2025-09-23 02:09:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008335714228451252 | lossAlign: 0
+2025-09-23 02:09:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0040515754371881485 | lossAlign: 0
+2025-09-23 02:09:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.074575215578079e-05 | lossAlign: 0
+2025-09-23 02:09:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.771627472015098e-05 | lossAlign: 0
+2025-09-23 02:09:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.655846062931232e-05 | lossAlign: 0
+2025-09-23 02:09:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001125130511354655 | lossAlign: 0
+2025-09-23 02:09:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.408072401129175e-06 | lossAlign: 0
+2025-09-23 02:09:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007976694032549858 | lossAlign: 0
+2025-09-23 02:09:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.208932750771055e-06 | lossAlign: 0
+2025-09-23 02:09:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031318774563260376 | lossAlign: 0
+2025-09-23 02:09:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001573877379996702 | lossAlign: 0
+2025-09-23 02:09:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.827096967754187e-06 | lossAlign: 0
+2025-09-23 02:09:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012426622561179101 | lossAlign: 0
+2025-09-23 02:09:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005234702839516103 | lossAlign: 0
+2025-09-23 02:09:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018824092694558203 | lossAlign: 0
+2025-09-23 02:09:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021940656006336212 | lossAlign: 0
+2025-09-23 02:09:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5606956367264502e-05 | lossAlign: 0
+2025-09-23 02:09:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001061265284079127 | lossAlign: 0
+2025-09-23 02:09:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014763232320547104 | lossAlign: 0
+2025-09-23 02:09:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000202770228497684 | lossAlign: 0
+2025-09-23 02:09:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.1266615628264844e-05 | lossAlign: 0
+2025-09-23 02:09:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.822266080533154e-05 | lossAlign: 0
+2025-09-23 02:09:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.0106355047319084e-06 | lossAlign: 0
+2025-09-23 02:09:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003488205838948488 | lossAlign: 0
+2025-09-23 02:09:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000995030626654625 | lossAlign: 0
+2025-09-23 02:09:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.740552741277497e-06 | lossAlign: 0
+2025-09-23 02:09:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.761975990026258e-05 | lossAlign: 0
+2025-09-23 02:09:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5341181753901765e-05 | lossAlign: 0
+2025-09-23 02:09:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005287773092277348 | lossAlign: 0
+2025-09-23 02:10:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022628999431617558 | lossAlign: 0
+2025-09-23 02:10:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.564669219078496e-05 | lossAlign: 0
+2025-09-23 02:10:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021410369663499296 | lossAlign: 0
+2025-09-23 02:10:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008216009009629488 | lossAlign: 0
+2025-09-23 02:10:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.297833947930485e-05 | lossAlign: 0
+2025-09-23 02:10:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8670765459537506e-05 | lossAlign: 0
+2025-09-23 02:10:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011582980368984863 | lossAlign: 0
+2025-09-23 02:10:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014208527281880379 | lossAlign: 0
+2025-09-23 02:10:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020051926549058408 | lossAlign: 0
+2025-09-23 02:10:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001542432582937181 | lossAlign: 0
+2025-09-23 02:10:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.476787141058594e-05 | lossAlign: 0
+2025-09-23 02:10:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00029580475529655814 | lossAlign: 0
+2025-09-23 02:10:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.973061393480748e-05 | lossAlign: 0
+2025-09-23 02:10:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010381732136011124 | lossAlign: 0
+2025-09-23 02:10:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003026817867066711 | lossAlign: 0
+2025-09-23 02:10:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.712345121835824e-05 | lossAlign: 0
+2025-09-23 02:10:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.400157922646031e-05 | lossAlign: 0
+2025-09-23 02:10:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010316145198885351 | lossAlign: 0
+2025-09-23 02:10:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.297542545828037e-05 | lossAlign: 0
+2025-09-23 02:10:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.479459362803027e-05 | lossAlign: 0
+2025-09-23 02:10:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7893118638312444e-05 | lossAlign: 0
+2025-09-23 02:10:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.132784619694576e-05 | lossAlign: 0
+2025-09-23 02:10:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.392134385649115e-05 | lossAlign: 0
+2025-09-23 02:10:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004188604361843318 | lossAlign: 0
+2025-09-23 02:10:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020372678409330547 | lossAlign: 0
+2025-09-23 02:10:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014973348879721016 | lossAlign: 0
+2025-09-23 02:10:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018342887051403522 | lossAlign: 0
+2025-09-23 02:10:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019671989139169455 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007878992473706603 | lossAlign: 0
+2025-09-23 02:10:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.788740514210076e-06 | lossAlign: 0
+2025-09-23 02:10:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.16771677514771e-05 | lossAlign: 0
+2025-09-23 02:10:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.0480411775643006e-05 | lossAlign: 0
+2025-09-23 02:11:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7884187400341034e-05 | lossAlign: 0
+2025-09-23 02:11:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019810661615338176 | lossAlign: 0
+2025-09-23 02:11:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.213760495185852e-05 | lossAlign: 0
+2025-09-23 02:11:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000307384500047192 | lossAlign: 0
+2025-09-23 02:11:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005549012566916645 | lossAlign: 0
+2025-09-23 02:11:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.62377759302035e-05 | lossAlign: 0
+2025-09-23 02:11:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.811768904910423e-06 | lossAlign: 0
+2025-09-23 02:11:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000428217084845528 | lossAlign: 0
+2025-09-23 02:11:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.415507621364668e-05 | lossAlign: 0
+2025-09-23 02:11:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020718187442980707 | lossAlign: 0
+2025-09-23 02:11:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.063150405883789e-06 | lossAlign: 0
+2025-09-23 02:11:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014606329204980284 | lossAlign: 0
+2025-09-23 02:11:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8495865990407765e-05 | lossAlign: 0
+2025-09-23 02:11:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4159414604364429e-05 | lossAlign: 0
+2025-09-23 02:11:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021035425015725195 | lossAlign: 0
+2025-09-23 02:11:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0094022400153335e-05 | lossAlign: 0
+2025-09-23 02:11:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.870699088613037e-05 | lossAlign: 0
+2025-09-23 02:11:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3218772210166208e-06 | lossAlign: 0
+2025-09-23 02:11:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8164125978946686e-05 | lossAlign: 0
+2025-09-23 02:11:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.1734939916059375e-05 | lossAlign: 0
+2025-09-23 02:11:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9908493161201477e-05 | lossAlign: 0
+2025-09-23 02:11:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.659007678739727e-05 | lossAlign: 0
+2025-09-23 02:11:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2260916011873633e-05 | lossAlign: 0
+2025-09-23 02:11:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.1600255826779176e-06 | lossAlign: 0
+2025-09-23 02:11:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003014870162587613 | lossAlign: 0
+2025-09-23 02:11:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018983746122103184 | lossAlign: 0
+2025-09-23 02:11:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.032506247611309e-06 | lossAlign: 0
+2025-09-23 02:11:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010406303044874221 | lossAlign: 0
+2025-09-23 02:11:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002305334637640044 | lossAlign: 0
+2025-09-23 02:11:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.237626075744629e-05 | lossAlign: 0
+2025-09-23 02:11:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014210676308721304 | lossAlign: 0
+2025-09-23 02:11:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.470336615573615e-05 | lossAlign: 0
+2025-09-23 02:11:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015728689031675458 | lossAlign: 0
+2025-09-23 02:11:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005138127016834915 | lossAlign: 0
+2025-09-23 02:11:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003542892402037978 | lossAlign: 0
+2025-09-23 02:11:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.452737867832184e-05 | lossAlign: 0
+2025-09-23 02:12:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001477869227528572 | lossAlign: 0
+2025-09-23 02:12:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00034099124604836106 | lossAlign: 0
+2025-09-23 02:12:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003185829846188426 | lossAlign: 0
+2025-09-23 02:12:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.182052725809626e-05 | lossAlign: 0
+2025-09-23 02:12:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0707685760280583e-05 | lossAlign: 0
+2025-09-23 02:12:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001000515985651873 | lossAlign: 0
+2025-09-23 02:12:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.006667874520645e-05 | lossAlign: 0
+2025-09-23 02:12:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.299621989252046e-05 | lossAlign: 0
+2025-09-23 02:12:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.314206206705421e-05 | lossAlign: 0
+2025-09-23 02:12:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005031518172472715 | lossAlign: 0
+2025-09-23 02:12:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016590431914664805 | lossAlign: 0
+2025-09-23 02:12:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.747784153849352e-05 | lossAlign: 0
+2025-09-23 02:12:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3642840713146143e-05 | lossAlign: 0
+2025-09-23 02:12:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00029074097983539104 | lossAlign: 0
+2025-09-23 02:12:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8279093385208398e-05 | lossAlign: 0
+2025-09-23 02:12:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011593995441216975 | lossAlign: 0
+2025-09-23 02:12:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.822467937832698e-05 | lossAlign: 0
+2025-09-23 02:12:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.142563506728038e-06 | lossAlign: 0
+2025-09-23 02:12:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.2402993383584544e-05 | lossAlign: 0
+2025-09-23 02:12:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004898533225059509 | lossAlign: 0
+2025-09-23 02:12:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00051103689474985 | lossAlign: 0
+2025-09-23 02:12:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.42657100292854e-05 | lossAlign: 0
+2025-09-23 02:12:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7162821425008588e-05 | lossAlign: 0
+2025-09-23 02:12:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.007602754223626e-05 | lossAlign: 0
+2025-09-23 02:12:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000132835004478693 | lossAlign: 0
+2025-09-23 02:12:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00042214375571347773 | lossAlign: 0
+2025-09-23 02:12:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.6425917389569804e-05 | lossAlign: 0
+2025-09-23 02:12:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7639249563217163e-05 | lossAlign: 0
+2025-09-23 02:12:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004702802747488022 | lossAlign: 0
+2025-09-23 02:12:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012757578224409372 | lossAlign: 0
+2025-09-23 02:12:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010913658479694277 | lossAlign: 0
+2025-09-23 02:12:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010013483552029356 | lossAlign: 0
+2025-09-23 02:13:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.002824269060511e-05 | lossAlign: 0
+2025-09-23 02:13:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002116362302331254 | lossAlign: 0
+2025-09-23 02:13:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021194660803303123 | lossAlign: 0
+2025-09-23 02:13:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010843005293281749 | lossAlign: 0
+2025-09-23 02:13:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.074187457561493e-05 | lossAlign: 0
+2025-09-23 02:13:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013000202307011932 | lossAlign: 0
+2025-09-23 02:13:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.46858984004939e-06 | lossAlign: 0
+2025-09-23 02:13:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015221405192278326 | lossAlign: 0
+2025-09-23 02:13:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.997928848140873e-05 | lossAlign: 0
+2025-09-23 02:13:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0031291544437408447 | lossAlign: 0
+2025-09-23 02:13:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00025899658794514835 | lossAlign: 0
+2025-09-23 02:13:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.006460219621658325 | lossAlign: 0
+2025-09-23 02:13:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.908462091814727e-05 | lossAlign: 0
+2025-09-23 02:13:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.567151725292206e-05 | lossAlign: 0
+2025-09-23 02:13:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012279200600460172 | lossAlign: 0
+2025-09-23 02:13:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.069074566359632e-05 | lossAlign: 0
+2025-09-23 02:13:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4738177419058047e-06 | lossAlign: 0
+2025-09-23 02:13:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005103368894197047 | lossAlign: 0
+2025-09-23 02:13:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00048377629718743265 | lossAlign: 0
+2025-09-23 02:13:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3581504137837328e-05 | lossAlign: 0
+2025-09-23 02:13:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002031422482104972 | lossAlign: 0
+2025-09-23 02:13:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1312385140627157e-05 | lossAlign: 0
+2025-09-23 02:13:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.469652438070625e-05 | lossAlign: 0
+2025-09-23 02:13:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7745018340065144e-05 | lossAlign: 0
+2025-09-23 02:13:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004326364491134882 | lossAlign: 0
+2025-09-23 02:13:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002579251304268837 | lossAlign: 0
+2025-09-23 02:13:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0027392965275794268 | lossAlign: 0
+2025-09-23 02:13:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.067097850362188e-06 | lossAlign: 0
+2025-09-23 02:13:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.374524673447013e-05 | lossAlign: 0
+2025-09-23 02:13:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.159503729781136e-05 | lossAlign: 0
+2025-09-23 02:13:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00037317900569178164 | lossAlign: 0
+2025-09-23 02:13:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023710541427135468 | lossAlign: 0
+2025-09-23 02:13:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5526047465973534e-05 | lossAlign: 0
+2025-09-23 02:13:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.006039282307029e-05 | lossAlign: 0
+2025-09-23 02:13:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.28674323100131e-05 | lossAlign: 0
+2025-09-23 02:13:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018136389553546906 | lossAlign: 0
+2025-09-23 02:14:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011620465375017375 | lossAlign: 0
+2025-09-23 02:14:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032829027622938156 | lossAlign: 0
+2025-09-23 02:14:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005641038878820837 | lossAlign: 0
+2025-09-23 02:14:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.872510311950464e-06 | lossAlign: 0
+2025-09-23 02:14:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9794753572787158e-05 | lossAlign: 0
+2025-09-23 02:14:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.619444032665342e-05 | lossAlign: 0
+2025-09-23 02:14:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.724906804971397e-05 | lossAlign: 0
+2025-09-23 02:14:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.949580109794624e-05 | lossAlign: 0
+2025-09-23 02:14:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014125251618679613 | lossAlign: 0
+2025-09-23 02:14:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012443290324881673 | lossAlign: 0
+2025-09-23 02:14:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3497268557548523e-05 | lossAlign: 0
+2025-09-23 02:14:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9605242161778733e-05 | lossAlign: 0
+2025-09-23 02:14:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.56542261922732e-06 | lossAlign: 0
+2025-09-23 02:14:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015797614469192922 | lossAlign: 0
+2025-09-23 02:14:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7524969229707494e-05 | lossAlign: 0
+2025-09-23 02:14:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.937957757851109e-05 | lossAlign: 0
+2025-09-23 02:14:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008728785905987024 | lossAlign: 0
+2025-09-23 02:14:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035783791099675 | lossAlign: 0
+2025-09-23 02:14:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.3427182137966156e-05 | lossAlign: 0
+2025-09-23 02:14:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018941386952064931 | lossAlign: 0
+2025-09-23 02:14:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.447708437917754e-05 | lossAlign: 0
+2025-09-23 02:14:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.381042087217793e-05 | lossAlign: 0
+2025-09-23 02:14:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.474789223721018e-05 | lossAlign: 0
+2025-09-23 02:14:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030404707649722695 | lossAlign: 0
+2025-09-23 02:14:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4122516404313501e-05 | lossAlign: 0
+2025-09-23 02:14:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1857100616907701e-05 | lossAlign: 0
+2025-09-23 02:14:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00046311799087561667 | lossAlign: 0
+2025-09-23 02:14:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007182256667874753 | lossAlign: 0
+2025-09-23 02:14:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005023254081606865 | lossAlign: 0
+2025-09-23 02:14:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001350115635432303 | lossAlign: 0
+2025-09-23 02:14:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3520240827347152e-05 | lossAlign: 0
+2025-09-23 02:14:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022125530813355 | lossAlign: 0
+2025-09-23 02:15:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.964631782262586e-05 | lossAlign: 0
+2025-09-23 02:15:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.255603693716694e-06 | lossAlign: 0
+2025-09-23 02:15:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019866511865984648 | lossAlign: 0
+2025-09-23 02:15:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032059382647275925 | lossAlign: 0
+2025-09-23 02:15:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.685273885726929e-06 | lossAlign: 0
+2025-09-23 02:15:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.574716293362144e-06 | lossAlign: 0
+2025-09-23 02:15:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.026534487726167e-05 | lossAlign: 0
+2025-09-23 02:15:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.581146175856702e-06 | lossAlign: 0
+2025-09-23 02:15:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002487287565600127 | lossAlign: 0
+2025-09-23 02:15:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003609619743656367 | lossAlign: 0
+2025-09-23 02:15:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0552860658208374e-05 | lossAlign: 0
+2025-09-23 02:15:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.6023302274988964e-05 | lossAlign: 0
+2025-09-23 02:15:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.996010001283139e-05 | lossAlign: 0
+2025-09-23 02:15:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.367902874946594e-05 | lossAlign: 0
+2025-09-23 02:15:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.956205662485445e-06 | lossAlign: 0
+2025-09-23 02:15:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005203514010645449 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023014377802610397 | lossAlign: 0
+2025-09-23 02:15:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001529801229480654 | lossAlign: 0
+2025-09-23 02:15:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.02407885203138e-05 | lossAlign: 0
+2025-09-23 02:15:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.9885846793768e-07 | lossAlign: 0
+2025-09-23 02:15:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2493132999225054e-06 | lossAlign: 0
+2025-09-23 02:15:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000194145628483966 | lossAlign: 0
+2025-09-23 02:15:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.188818512484431e-05 | lossAlign: 0
+2025-09-23 02:15:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.914511398761533e-05 | lossAlign: 0
+2025-09-23 02:15:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1176608697714983e-06 | lossAlign: 0
+2025-09-23 02:15:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012762355618178844 | lossAlign: 0
+2025-09-23 02:15:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014969972835388035 | lossAlign: 0
+2025-09-23 02:15:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001702492736512795 | lossAlign: 0
+2025-09-23 02:15:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.1565170906542335e-06 | lossAlign: 0
+2025-09-23 02:15:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009051439119502902 | lossAlign: 0
+2025-09-23 02:15:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.069711106538307e-05 | lossAlign: 0
+2025-09-23 02:15:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.6426343033090234e-05 | lossAlign: 0
+2025-09-23 02:16:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00029616375104524195 | lossAlign: 0
+2025-09-23 02:16:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.52005832712166e-05 | lossAlign: 0
+2025-09-23 02:16:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0213231689704116e-05 | lossAlign: 0
+2025-09-23 02:16:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017119571566581726 | lossAlign: 0
+2025-09-23 02:16:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.723204150039237e-06 | lossAlign: 0
+2025-09-23 02:16:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002013782737776637 | lossAlign: 0
+2025-09-23 02:16:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7888843507971615e-05 | lossAlign: 0
+2025-09-23 02:16:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.431245128624141e-05 | lossAlign: 0
+2025-09-23 02:16:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.1035393476486206e-05 | lossAlign: 0
+2025-09-23 02:16:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011253422126173973 | lossAlign: 0
+2025-09-23 02:16:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018004894081968814 | lossAlign: 0
+2025-09-23 02:16:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.829052724948269e-07 | lossAlign: 0
+2025-09-23 02:16:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.364357927348465e-05 | lossAlign: 0
+2025-09-23 02:16:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.105492917005904e-05 | lossAlign: 0
+2025-09-23 02:16:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7717038594564656e-06 | lossAlign: 0
+2025-09-23 02:16:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010552238672971725 | lossAlign: 0
+2025-09-23 02:16:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4390945580089465e-05 | lossAlign: 0
+2025-09-23 02:16:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.3977390305371955e-05 | lossAlign: 0
+2025-09-23 02:16:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016984532121568918 | lossAlign: 0
+2025-09-23 02:16:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1636151612037793e-05 | lossAlign: 0
+2025-09-23 02:16:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003802842926234007 | lossAlign: 0
+2025-09-23 02:16:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.461237353505567e-05 | lossAlign: 0
+2025-09-23 02:16:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.144830983132124e-05 | lossAlign: 0
+2025-09-23 02:16:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014697559527121484 | lossAlign: 0
+2025-09-23 02:16:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1040317986044101e-05 | lossAlign: 0
+2025-09-23 02:16:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00269755139015615 | lossAlign: 0
+2025-09-23 02:16:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0017826829571276903 | lossAlign: 0
+2025-09-23 02:16:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005500871338881552 | lossAlign: 0
+2025-09-23 02:16:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.541489736060612e-05 | lossAlign: 0
+2025-09-23 02:16:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000202300027012825 | lossAlign: 0
+2025-09-23 02:16:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.021705973893404007 | lossAlign: 0
+2025-09-23 02:16:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014135148376226425 | lossAlign: 0
+2025-09-23 02:16:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018239679047837853 | lossAlign: 0
+2025-09-23 02:16:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.248209602839779e-05 | lossAlign: 0
+2025-09-23 02:16:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.148193046508823e-06 | lossAlign: 0
+2025-09-23 02:16:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002691395638976246 | lossAlign: 0
+2025-09-23 02:17:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.2462161218281835e-05 | lossAlign: 0
+2025-09-23 02:17:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9002587325521745e-05 | lossAlign: 0
+2025-09-23 02:17:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001918878551805392 | lossAlign: 0
+2025-09-23 02:17:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.053674638271332e-05 | lossAlign: 0
+2025-09-23 02:17:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.136661977507174e-05 | lossAlign: 0
+2025-09-23 02:17:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019631689065136015 | lossAlign: 0
+2025-09-23 02:17:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003593677538447082 | lossAlign: 0
+2025-09-23 02:17:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9494985938072205e-06 | lossAlign: 0
+2025-09-23 02:17:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.422856050543487e-05 | lossAlign: 0
+2025-09-23 02:17:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.931376002379693e-06 | lossAlign: 0
+2025-09-23 02:17:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.129484583856538e-05 | lossAlign: 0
+2025-09-23 02:17:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00042967835906893015 | lossAlign: 0
+2025-09-23 02:17:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010424377396702766 | lossAlign: 0
+2025-09-23 02:17:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.714619015227072e-05 | lossAlign: 0
+2025-09-23 02:17:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011336034367559478 | lossAlign: 0
+2025-09-23 02:17:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004755314439535141 | lossAlign: 0
+2025-09-23 02:17:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016118335770443082 | lossAlign: 0
+2025-09-23 02:17:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.467513594543561e-05 | lossAlign: 0
+2025-09-23 02:17:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7667403881205246e-05 | lossAlign: 0
+2025-09-23 02:17:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.528739661211148e-05 | lossAlign: 0
+2025-09-23 02:17:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8955239283968695e-05 | lossAlign: 0
+2025-09-23 02:17:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4333955959955347e-06 | lossAlign: 0
+2025-09-23 02:17:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005593450041487813 | lossAlign: 0
+2025-09-23 02:17:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4793677109992132e-05 | lossAlign: 0
+2025-09-23 02:17:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2472640946725733e-06 | lossAlign: 0
+2025-09-23 02:17:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017804336675908417 | lossAlign: 0
+2025-09-23 02:17:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.58433922479162e-05 | lossAlign: 0
+2025-09-23 02:17:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00283032120205462 | lossAlign: 0
+2025-09-23 02:17:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.423286423436366e-05 | lossAlign: 0
+2025-09-23 02:17:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.334988029266242e-06 | lossAlign: 0
+2025-09-23 02:17:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.7331220887135714e-05 | lossAlign: 0
+2025-09-23 02:17:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.6315061151981354e-05 | lossAlign: 0
+2025-09-23 02:18:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5985686079366133e-05 | lossAlign: 0
+2025-09-23 02:18:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.444570317398757e-05 | lossAlign: 0
+2025-09-23 02:18:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.678625817992724e-06 | lossAlign: 0
+2025-09-23 02:18:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5443021766259335e-05 | lossAlign: 0
+2025-09-23 02:18:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.456638220697641e-05 | lossAlign: 0
+2025-09-23 02:18:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.928559287189273e-06 | lossAlign: 0
+2025-09-23 02:18:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2148329662741162e-05 | lossAlign: 0
+2025-09-23 02:18:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032150649349205196 | lossAlign: 0
+2025-09-23 02:18:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7841138035000768e-06 | lossAlign: 0
+2025-09-23 02:18:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026820256607607007 | lossAlign: 0
+2025-09-23 02:18:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.29844653303735e-05 | lossAlign: 0
+2025-09-23 02:18:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.178914482759865e-07 | lossAlign: 0
+2025-09-23 02:18:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.966016083722934e-05 | lossAlign: 0
+2025-09-23 02:18:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9888844892411726e-06 | lossAlign: 0
+2025-09-23 02:18:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012822171265725046 | lossAlign: 0
+2025-09-23 02:18:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002393160481005907 | lossAlign: 0
+2025-09-23 02:18:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016833553090691566 | lossAlign: 0
+2025-09-23 02:18:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.956305903964676e-05 | lossAlign: 0
+2025-09-23 02:18:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.7916793593904004e-05 | lossAlign: 0
+2025-09-23 02:18:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.492209078918677e-06 | lossAlign: 0
+2025-09-23 02:18:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.917804396129213e-06 | lossAlign: 0
+2025-09-23 02:18:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2708286703855265e-05 | lossAlign: 0
+2025-09-23 02:18:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.891670197248459e-05 | lossAlign: 0
+2025-09-23 02:18:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.903648227307713e-06 | lossAlign: 0
+2025-09-23 02:18:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.297723641386256e-06 | lossAlign: 0
+2025-09-23 02:18:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005908756284043193 | lossAlign: 0
+2025-09-23 02:18:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.643931894563138e-06 | lossAlign: 0
+2025-09-23 02:18:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021633932192344218 | lossAlign: 0
+2025-09-23 02:18:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8495787773863412e-06 | lossAlign: 0
+2025-09-23 02:18:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008709118701517582 | lossAlign: 0
+2025-09-23 02:18:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.1704978027846664e-05 | lossAlign: 0
+2025-09-23 02:18:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004494004882872105 | lossAlign: 0
+2025-09-23 02:18:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030478998087346554 | lossAlign: 0
+2025-09-23 02:18:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.144827395677567e-05 | lossAlign: 0
+2025-09-23 02:18:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014302063209470361 | lossAlign: 0
+2025-09-23 02:18:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00044126075226813555 | lossAlign: 0
+2025-09-23 02:19:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010860159818548709 | lossAlign: 0
+2025-09-23 02:19:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.345814760308713e-06 | lossAlign: 0
+2025-09-23 02:19:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.644706445513293e-06 | lossAlign: 0
+2025-09-23 02:19:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3526192308054306e-05 | lossAlign: 0
+2025-09-23 02:19:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041316813440062106 | lossAlign: 0
+2025-09-23 02:19:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4006614946993068e-05 | lossAlign: 0
+2025-09-23 02:19:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6384368538856506e-05 | lossAlign: 0
+2025-09-23 02:19:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026406088727526367 | lossAlign: 0
+2025-09-23 02:19:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.33306891459506e-05 | lossAlign: 0
+2025-09-23 02:19:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.554412539117038e-05 | lossAlign: 0
+2025-09-23 02:19:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011692701082210988 | lossAlign: 0
+2025-09-23 02:19:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.155014034447959e-06 | lossAlign: 0
+2025-09-23 02:19:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011326947424095124 | lossAlign: 0
+2025-09-23 02:19:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8523002129077213e-06 | lossAlign: 0
+2025-09-23 02:19:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.546296167973196e-06 | lossAlign: 0
+2025-09-23 02:19:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.8789748941781e-05 | lossAlign: 0
+2025-09-23 02:19:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.431118673484889e-06 | lossAlign: 0
+2025-09-23 02:19:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1793902103818255e-06 | lossAlign: 0
+2025-09-23 02:19:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00038737343857064843 | lossAlign: 0
+2025-09-23 02:19:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.159370968816802e-05 | lossAlign: 0
+2025-09-23 02:19:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.248890490998747e-06 | lossAlign: 0
+2025-09-23 02:19:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7595291410543723e-06 | lossAlign: 0
+2025-09-23 02:19:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.697540255918284e-06 | lossAlign: 0
+2025-09-23 02:19:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.050388325704262e-05 | lossAlign: 0
+2025-09-23 02:19:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.194797035481315e-06 | lossAlign: 0
+2025-09-23 02:19:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010692221985664219 | lossAlign: 0
+2025-09-23 02:19:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030027299653738737 | lossAlign: 0
+2025-09-23 02:19:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.1144539611414075e-05 | lossAlign: 0
+2025-09-23 02:19:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012113586853956804 | lossAlign: 0
+2025-09-23 02:19:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.826545591640752e-06 | lossAlign: 0
+2025-09-23 02:19:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.216338998550782e-06 | lossAlign: 0
+2025-09-23 02:19:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.60091087006731e-06 | lossAlign: 0
+2025-09-23 02:20:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.871799218468368e-05 | lossAlign: 0
+2025-09-23 02:20:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.624515061848797e-05 | lossAlign: 0
+2025-09-23 02:20:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0189994504326023e-06 | lossAlign: 0
+2025-09-23 02:20:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.044249180878978e-06 | lossAlign: 0
+2025-09-23 02:20:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7195212421938777e-05 | lossAlign: 0
+2025-09-23 02:20:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020415670587681234 | lossAlign: 0
+2025-09-23 02:20:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.264856660389341e-06 | lossAlign: 0
+2025-09-23 02:20:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.240089426981285e-05 | lossAlign: 0
+2025-09-23 02:20:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.613586032879539e-06 | lossAlign: 0
+2025-09-23 02:20:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.008470580913126469 | lossAlign: 0
+2025-09-23 02:20:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.215946425276343e-06 | lossAlign: 0
+2025-09-23 02:20:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.38158951207879e-06 | lossAlign: 0
+2025-09-23 02:20:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2530945241451263e-05 | lossAlign: 0
+2025-09-23 02:20:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.449567470350303e-05 | lossAlign: 0
+2025-09-23 02:20:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00043997238390147686 | lossAlign: 0
+2025-09-23 02:20:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003163058718200773 | lossAlign: 0
+2025-09-23 02:20:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.665720815770328e-05 | lossAlign: 0
+2025-09-23 02:20:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008029629825614393 | lossAlign: 0
+2025-09-23 02:20:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.691123831435107e-05 | lossAlign: 0
+2025-09-23 02:20:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018045686883851886 | lossAlign: 0
+2025-09-23 02:20:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.48329045259743e-05 | lossAlign: 0
+2025-09-23 02:20:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0257224352681078e-05 | lossAlign: 0
+2025-09-23 02:20:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.571151657728478e-05 | lossAlign: 0
+2025-09-23 02:20:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.005444811191409826 | lossAlign: 0
+2025-09-23 02:20:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.1369877433462534e-06 | lossAlign: 0
+2025-09-23 02:20:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.067326128482819e-06 | lossAlign: 0
+2025-09-23 02:20:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.517154153902084e-05 | lossAlign: 0
+2025-09-23 02:20:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2986741896602325e-05 | lossAlign: 0
+2025-09-23 02:20:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.579043398844078e-05 | lossAlign: 0
+2025-09-23 02:20:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6968095906122471e-06 | lossAlign: 0
+2025-09-23 02:20:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011835367331514135 | lossAlign: 0
+2025-09-23 02:20:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.973693911684677e-05 | lossAlign: 0
+2025-09-23 02:20:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.855705916881561e-06 | lossAlign: 0
+2025-09-23 02:20:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.874107955605723e-06 | lossAlign: 0
+2025-09-23 02:20:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004438790783751756 | lossAlign: 0
+2025-09-23 02:20:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2015539141430054e-06 | lossAlign: 0
+2025-09-23 02:21:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9700297343661077e-05 | lossAlign: 0
+2025-09-23 02:21:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001221941492985934 | lossAlign: 0
+2025-09-23 02:21:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.709216904710047e-06 | lossAlign: 0
+2025-09-23 02:21:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.590621306808316e-06 | lossAlign: 0
+2025-09-23 02:21:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.533332321443595e-05 | lossAlign: 0
+2025-09-23 02:21:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.8209462218219414e-05 | lossAlign: 0
+2025-09-23 02:21:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.475873763316486e-07 | lossAlign: 0
+2025-09-23 02:21:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.532105999212945e-06 | lossAlign: 0
+2025-09-23 02:21:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4937093257904053e-05 | lossAlign: 0
+2025-09-23 02:21:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.9838134145829827e-05 | lossAlign: 0
+2025-09-23 02:21:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.059992402791977e-05 | lossAlign: 0
+2025-09-23 02:21:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.403458660817705e-05 | lossAlign: 0
+2025-09-23 02:21:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0030777037609368563 | lossAlign: 0
+2025-09-23 02:21:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.7478467321489e-05 | lossAlign: 0
+2025-09-23 02:21:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4878208932932466e-05 | lossAlign: 0
+2025-09-23 02:21:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015792346675880253 | lossAlign: 0
+2025-09-23 02:21:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.122039733076235e-06 | lossAlign: 0
+2025-09-23 02:21:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.932494342327118e-06 | lossAlign: 0
+2025-09-23 02:21:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1811964213848114e-05 | lossAlign: 0
+2025-09-23 02:21:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017179176211357117 | lossAlign: 0
+2025-09-23 02:21:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.876465133449528e-06 | lossAlign: 0
+2025-09-23 02:21:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018644332885742188 | lossAlign: 0
+2025-09-23 02:21:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.356620724545792e-05 | lossAlign: 0
+2025-09-23 02:21:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.589557647705078e-06 | lossAlign: 0
+2025-09-23 02:21:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.192611519712955e-06 | lossAlign: 0
+2025-09-23 02:21:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7829722714377567e-06 | lossAlign: 0
+2025-09-23 02:21:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0020083370618522167 | lossAlign: 0
+2025-09-23 02:21:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.53941402156488e-06 | lossAlign: 0
+2025-09-23 02:21:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003665178664959967 | lossAlign: 0
+2025-09-23 02:21:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.052596002817154e-05 | lossAlign: 0
+2025-09-23 02:21:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008028660668060184 | lossAlign: 0
+2025-09-23 02:21:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.15885990858078e-05 | lossAlign: 0
+2025-09-23 02:22:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.456852133851498e-05 | lossAlign: 0
+2025-09-23 02:22:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00021363701671361923 | lossAlign: 0
+2025-09-23 02:22:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.547510126139969e-05 | lossAlign: 0
+2025-09-23 02:22:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.2207855333108455e-05 | lossAlign: 0
+2025-09-23 02:22:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.025611820499762e-06 | lossAlign: 0
+2025-09-23 02:22:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.96023948371294e-07 | lossAlign: 0
+2025-09-23 02:22:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.707313589984551e-05 | lossAlign: 0
+2025-09-23 02:22:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.641864456469193e-05 | lossAlign: 0
+2025-09-23 02:22:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00035037787165492773 | lossAlign: 0
+2025-09-23 02:22:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002098040422424674 | lossAlign: 0
+2025-09-23 02:22:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.738258550991304e-06 | lossAlign: 0
+2025-09-23 02:22:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00024251332797575742 | lossAlign: 0
+2025-09-23 02:22:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015600457845721394 | lossAlign: 0
+2025-09-23 02:22:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.550609497120604e-05 | lossAlign: 0
+2025-09-23 02:22:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001035155262798071 | lossAlign: 0
+2025-09-23 02:22:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005128118791617453 | lossAlign: 0
+2025-09-23 02:22:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018670442514121532 | lossAlign: 0
+2025-09-23 02:22:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1601448022702243e-05 | lossAlign: 0
+2025-09-23 02:22:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.2165356969926506e-05 | lossAlign: 0
+2025-09-23 02:22:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.626916052075103e-05 | lossAlign: 0
+2025-09-23 02:22:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.781550028885249e-05 | lossAlign: 0
+2025-09-23 02:22:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014312287385109812 | lossAlign: 0
+2025-09-23 02:22:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026608817279338837 | lossAlign: 0
+2025-09-23 02:22:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002084178850054741 | lossAlign: 0
+2025-09-23 02:22:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0678010767151136e-05 | lossAlign: 0
+2025-09-23 02:22:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.162351489067078e-06 | lossAlign: 0
+2025-09-23 02:22:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014579105481971055 | lossAlign: 0
+2025-09-23 02:22:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.960321040125564e-05 | lossAlign: 0
+2025-09-23 02:22:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4554977497027721e-05 | lossAlign: 0
+2025-09-23 02:22:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002508087200112641 | lossAlign: 0
+2025-09-23 02:22:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8676122635952197e-05 | lossAlign: 0
+2025-09-23 02:22:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018464861204847693 | lossAlign: 0
+2025-09-23 02:22:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00026763862115330994 | lossAlign: 0
+2025-09-23 02:22:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.988875323557295e-05 | lossAlign: 0
+2025-09-23 02:22:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.853282083175145e-05 | lossAlign: 0
+2025-09-23 02:22:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.189704825170338e-05 | lossAlign: 0
+2025-09-23 02:23:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.8757325455662794e-06 | lossAlign: 0
+2025-09-23 02:23:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004215346125420183 | lossAlign: 0
+2025-09-23 02:23:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001160021754913032 | lossAlign: 0
+2025-09-23 02:23:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.025004927068948746 | lossAlign: 0
+2025-09-23 02:23:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.527051361146732e-07 | lossAlign: 0
+2025-09-23 02:23:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.540984420804307e-05 | lossAlign: 0
+2025-09-23 02:23:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7333984942524694e-05 | lossAlign: 0
+2025-09-23 02:23:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.368135423897911e-07 | lossAlign: 0
+2025-09-23 02:23:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4677880244562402e-05 | lossAlign: 0
+2025-09-23 02:23:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.217954357154667e-05 | lossAlign: 0
+2025-09-23 02:23:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.8452900955453515e-05 | lossAlign: 0
+2025-09-23 02:23:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013074421440251172 | lossAlign: 0
+2025-09-23 02:23:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.074546738294885e-05 | lossAlign: 0
+2025-09-23 02:23:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.91596392748761e-06 | lossAlign: 0
+2025-09-23 02:23:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001129114767536521 | lossAlign: 0
+2025-09-23 02:23:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010495036840438843 | lossAlign: 0
+2025-09-23 02:23:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010553840547800064 | lossAlign: 0
+2025-09-23 02:23:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00023013110330794007 | lossAlign: 0
+2025-09-23 02:23:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002396879717707634 | lossAlign: 0
+2025-09-23 02:23:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.827758963685483e-06 | lossAlign: 0
+2025-09-23 02:23:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017162412405014038 | lossAlign: 0
+2025-09-23 02:23:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013527019182220101 | lossAlign: 0
+2025-09-23 02:23:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015107223589438945 | lossAlign: 0
+2025-09-23 02:23:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9001006876351312e-05 | lossAlign: 0
+2025-09-23 02:23:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014893825573381037 | lossAlign: 0
+2025-09-23 02:23:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001319853327004239 | lossAlign: 0
+2025-09-23 02:23:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6199322999455035e-05 | lossAlign: 0
+2025-09-23 02:23:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.693874017102644e-05 | lossAlign: 0
+2025-09-23 02:23:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.973098526126705e-05 | lossAlign: 0
+2025-09-23 02:23:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.779098475817591e-05 | lossAlign: 0
+2025-09-23 02:23:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.329736061161384e-05 | lossAlign: 0
+2025-09-23 02:23:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.7231445730867563e-06 | lossAlign: 0
+2025-09-23 02:24:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022223591804504395 | lossAlign: 0
+2025-09-23 02:24:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014174362877383828 | lossAlign: 0
+2025-09-23 02:24:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.76837158203125e-05 | lossAlign: 0
+2025-09-23 02:24:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014719624596182257 | lossAlign: 0
+2025-09-23 02:24:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.906393587589264e-05 | lossAlign: 0
+2025-09-23 02:24:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8250708510313416e-06 | lossAlign: 0
+2025-09-23 02:24:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.206152996426681e-06 | lossAlign: 0
+2025-09-23 02:24:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.747451268689474e-06 | lossAlign: 0
+2025-09-23 02:24:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008083877619355917 | lossAlign: 0
+2025-09-23 02:24:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003545455983839929 | lossAlign: 0
+2025-09-23 02:24:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.292087083333172e-05 | lossAlign: 0
+2025-09-23 02:24:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.3926578453247203e-06 | lossAlign: 0
+2025-09-23 02:24:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.561552850645967e-05 | lossAlign: 0
+2025-09-23 02:24:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012997693556826562 | lossAlign: 0
+2025-09-23 02:24:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.244067430496216e-06 | lossAlign: 0
+2025-09-23 02:24:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.011483608541312e-06 | lossAlign: 0
+2025-09-23 02:24:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.580905882292427e-05 | lossAlign: 0
+2025-09-23 02:24:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3403892808128148e-05 | lossAlign: 0
+2025-09-23 02:24:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0179148375755176e-05 | lossAlign: 0
+2025-09-23 02:24:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.7474258937872946e-05 | lossAlign: 0
+2025-09-23 02:24:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.76837158203125e-07 | lossAlign: 0
+2025-09-23 02:24:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.30093995318748e-05 | lossAlign: 0
+2025-09-23 02:24:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.158828909974545e-06 | lossAlign: 0
+2025-09-23 02:24:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00041787774534896016 | lossAlign: 0
+2025-09-23 02:24:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0022161242086440325 | lossAlign: 0
+2025-09-23 02:24:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004295894410461187 | lossAlign: 0
+2025-09-23 02:24:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.76150734256953e-05 | lossAlign: 0
+2025-09-23 02:24:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1353265563229797e-06 | lossAlign: 0
+2025-09-23 02:24:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0198463718988933e-05 | lossAlign: 0
+2025-09-23 02:24:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010282223956892267 | lossAlign: 0
+2025-09-23 02:24:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003772202879190445 | lossAlign: 0
+2025-09-23 02:24:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9147511920891702e-05 | lossAlign: 0
+2025-09-23 02:25:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.254044150300615e-06 | lossAlign: 0
+2025-09-23 02:25:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002273417339893058 | lossAlign: 0
+2025-09-23 02:25:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016427607624791563 | lossAlign: 0
+2025-09-23 02:25:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.343755664303899e-05 | lossAlign: 0
+2025-09-23 02:25:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0014590478967875242 | lossAlign: 0
+2025-09-23 02:25:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011739769979612902 | lossAlign: 0
+2025-09-23 02:25:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011973749496974051 | lossAlign: 0
+2025-09-23 02:25:08 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.072355270385742e-05 | lossAlign: 0
+2025-09-23 02:25:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.880812674760818e-05 | lossAlign: 0
+2025-09-23 02:25:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.759654631125159e-07 | lossAlign: 0
+2025-09-23 02:25:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.336593651212752e-05 | lossAlign: 0
+2025-09-23 02:25:15 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4704324207268655e-05 | lossAlign: 0
+2025-09-23 02:25:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025437078438699245 | lossAlign: 0
+2025-09-23 02:25:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4724770153407007e-05 | lossAlign: 0
+2025-09-23 02:25:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00348664284683764 | lossAlign: 0
+2025-09-23 02:25:22 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.381652878597379e-05 | lossAlign: 0
+2025-09-23 02:25:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015064977924339473 | lossAlign: 0
+2025-09-23 02:25:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1002156245231163e-06 | lossAlign: 0
+2025-09-23 02:25:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4538039724575356e-06 | lossAlign: 0
+2025-09-23 02:25:29 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.330013275146484e-05 | lossAlign: 0
+2025-09-23 02:25:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0018864684971049428 | lossAlign: 0
+2025-09-23 02:25:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9061379134655e-05 | lossAlign: 0
+2025-09-23 02:25:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0015104797203093767 | lossAlign: 0
+2025-09-23 02:25:36 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002805940748658031 | lossAlign: 0
+2025-09-23 02:25:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002546859032008797 | lossAlign: 0
+2025-09-23 02:25:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.7176145017147064e-05 | lossAlign: 0
+2025-09-23 02:25:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003251696762163192 | lossAlign: 0
+2025-09-23 02:25:43 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.203353404998779e-05 | lossAlign: 0
+2025-09-23 02:25:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.649307316460181e-05 | lossAlign: 0
+2025-09-23 02:25:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.562436566222459e-05 | lossAlign: 0
+2025-09-23 02:25:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.772070489409089e-07 | lossAlign: 0
+2025-09-23 02:25:50 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2624831470020581e-05 | lossAlign: 0
+2025-09-23 02:25:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.6846417060587555e-05 | lossAlign: 0
+2025-09-23 02:25:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5044775864225812e-05 | lossAlign: 0
+2025-09-23 02:25:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.332265911623836e-05 | lossAlign: 0
+2025-09-23 02:25:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3973031855130102e-05 | lossAlign: 0
+2025-09-23 02:26:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.748793005797779e-06 | lossAlign: 0
+2025-09-23 02:26:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005896157817915082 | lossAlign: 0
+2025-09-23 02:26:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9887597773049492e-06 | lossAlign: 0
+2025-09-23 02:26:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.5276501370826736e-05 | lossAlign: 0
+2025-09-23 02:26:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.6126306187943555e-06 | lossAlign: 0
+2025-09-23 02:26:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006999830948188901 | lossAlign: 0
+2025-09-23 02:26:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8569849999039434e-05 | lossAlign: 0
+2025-09-23 02:26:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.2701491363695823e-06 | lossAlign: 0
+2025-09-23 02:26:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.51366429135669e-06 | lossAlign: 0
+2025-09-23 02:26:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.34149990521837e-05 | lossAlign: 0
+2025-09-23 02:26:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.038955699390499e-06 | lossAlign: 0
+2025-09-23 02:26:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.93234404832765e-06 | lossAlign: 0
+2025-09-23 02:26:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015241987421177328 | lossAlign: 0
+2025-09-23 02:26:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0003319150418974e-05 | lossAlign: 0
+2025-09-23 02:26:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.060900432203198e-06 | lossAlign: 0
+2025-09-23 02:26:26 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011146837641717866 | lossAlign: 0
+2025-09-23 02:26:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.452656089095399e-05 | lossAlign: 0
+2025-09-23 02:26:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.452011232089717e-06 | lossAlign: 0
+2025-09-23 02:26:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002823514223564416 | lossAlign: 0
+2025-09-23 02:26:33 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010250027844449505 | lossAlign: 0
+2025-09-23 02:26:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.506624438567087e-05 | lossAlign: 0
+2025-09-23 02:26:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007884232327342033 | lossAlign: 0
+2025-09-23 02:26:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.14316187845543e-05 | lossAlign: 0
+2025-09-23 02:26:40 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.669048262760043e-05 | lossAlign: 0
+2025-09-23 02:26:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1670973663058248e-06 | lossAlign: 0
+2025-09-23 02:26:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.441757482709363e-06 | lossAlign: 0
+2025-09-23 02:26:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4162063735057018e-06 | lossAlign: 0
+2025-09-23 02:26:47 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00045923361903987825 | lossAlign: 0
+2025-09-23 02:26:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3518333616957534e-05 | lossAlign: 0
+2025-09-23 02:26:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.915875175967813e-05 | lossAlign: 0
+2025-09-23 02:26:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005892966873943806 | lossAlign: 0
+2025-09-23 02:26:54 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016301166033372283 | lossAlign: 0
+2025-09-23 02:27:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5498177162953652e-05 | lossAlign: 0
+2025-09-23 02:27:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018565617210697383 | lossAlign: 0
+2025-09-23 02:27:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.363448963180417e-06 | lossAlign: 0
+2025-09-23 02:27:01 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.851406290777959e-05 | lossAlign: 0
+2025-09-23 02:27:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.07618881581584e-06 | lossAlign: 0
+2025-09-23 02:27:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2584559044626076e-05 | lossAlign: 0
+2025-09-23 02:27:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8796195692848414e-05 | lossAlign: 0
+2025-09-23 02:27:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.940552990883589e-05 | lossAlign: 0
+2025-09-23 02:27:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013051005080342293 | lossAlign: 0
+2025-09-23 02:27:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.370812242385e-05 | lossAlign: 0
+2025-09-23 02:27:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.711004268960096e-05 | lossAlign: 0
+2025-09-23 02:27:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.71723921893863e-06 | lossAlign: 0
+2025-09-23 02:27:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.236496796598658e-05 | lossAlign: 0
+2025-09-23 02:27:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016370171215385199 | lossAlign: 0
+2025-09-23 02:27:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001621972769498825 | lossAlign: 0
+2025-09-23 02:27:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.558253400929971e-06 | lossAlign: 0
+2025-09-23 02:27:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007637710659764707 | lossAlign: 0
+2025-09-23 02:27:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.002527338219806552 | lossAlign: 0
+2025-09-23 02:27:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6428793717059307e-05 | lossAlign: 0
+2025-09-23 02:27:30 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.33962553517631e-07 | lossAlign: 0
+2025-09-23 02:27:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7138417863170616e-05 | lossAlign: 0
+2025-09-23 02:27:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002363028470426798 | lossAlign: 0
+2025-09-23 02:27:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.4740992305160034e-06 | lossAlign: 0
+2025-09-23 02:27:37 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2023107956338208e-05 | lossAlign: 0
+2025-09-23 02:27:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.885910261189565e-05 | lossAlign: 0
+2025-09-23 02:27:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012689653085544705 | lossAlign: 0
+2025-09-23 02:27:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4214505174313672e-05 | lossAlign: 0
+2025-09-23 02:27:44 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9433340387186036e-06 | lossAlign: 0
+2025-09-23 02:27:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.887220479256939e-06 | lossAlign: 0
+2025-09-23 02:27:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.6951038206752855e-06 | lossAlign: 0
+2025-09-23 02:27:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000534213671926409 | lossAlign: 0
+2025-09-23 02:27:51 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.745220601558685e-05 | lossAlign: 0
+2025-09-23 02:27:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5321187674999237e-05 | lossAlign: 0
+2025-09-23 02:27:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011246148642385378 | lossAlign: 0
+2025-09-23 02:27:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0028410989325493574 | lossAlign: 0
+2025-09-23 02:27:58 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.494234210345894e-05 | lossAlign: 0
+2025-09-23 02:28:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.345390622504056e-05 | lossAlign: 0
+2025-09-23 02:28:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0093193345237523e-05 | lossAlign: 0
+2025-09-23 02:28:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0796419701364357e-05 | lossAlign: 0
+2025-09-23 02:28:05 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7418635252397507e-05 | lossAlign: 0
+2025-09-23 02:28:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000270929594989866 | lossAlign: 0
+2025-09-23 02:28:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.612498848175164e-06 | lossAlign: 0
+2025-09-23 02:28:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007396251312457025 | lossAlign: 0
+2025-09-23 02:28:12 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0752151360502467e-05 | lossAlign: 0
+2025-09-23 02:28:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.5539625969249755e-05 | lossAlign: 0
+2025-09-23 02:28:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.831544043147005e-05 | lossAlign: 0
+2025-09-23 02:28:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5655517927370965e-05 | lossAlign: 0
+2025-09-23 02:28:19 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.0025973652955145e-05 | lossAlign: 0
+2025-09-23 02:28:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.947088746121153e-05 | lossAlign: 0
+2025-09-23 02:28:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.0690421883482486e-05 | lossAlign: 0
+2025-09-23 02:28:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.9298015407403e-06 | lossAlign: 0
+2025-09-23 02:28:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4431174097117037e-05 | lossAlign: 0
+2025-09-23 02:28:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005591369699686766 | lossAlign: 0
+2025-09-23 02:28:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.052338095381856e-05 | lossAlign: 0
+2025-09-23 02:28:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6726347641670145e-05 | lossAlign: 0
+2025-09-23 02:28:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4427185305976309e-05 | lossAlign: 0
+2025-09-23 02:28:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.0626455049496144e-05 | lossAlign: 0
+2025-09-23 02:28:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.288078369223513e-05 | lossAlign: 0
+2025-09-23 02:28:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.30481088894885e-05 | lossAlign: 0
+2025-09-23 02:28:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.301995694637299e-05 | lossAlign: 0
+2025-09-23 02:28:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004660177219193429 | lossAlign: 0
+2025-09-23 02:28:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.784652562899282e-06 | lossAlign: 0
+2025-09-23 02:28:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2129934222903103e-05 | lossAlign: 0
+2025-09-23 02:28:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.146936069242656e-05 | lossAlign: 0
+2025-09-23 02:28:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006458421121351421 | lossAlign: 0
+2025-09-23 02:28:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.06672653905116e-06 | lossAlign: 0
+2025-09-23 02:28:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9135437469230965e-05 | lossAlign: 0
+2025-09-23 02:28:55 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.042641654043109e-06 | lossAlign: 0
+2025-09-23 02:29:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000492419523652643 | lossAlign: 0
+2025-09-23 02:29:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.467139463784406e-05 | lossAlign: 0
+2025-09-23 02:29:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.079707302182214e-06 | lossAlign: 0
+2025-09-23 02:29:02 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.4516615010506939e-05 | lossAlign: 0
+2025-09-23 02:29:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.532028545625508e-05 | lossAlign: 0
+2025-09-23 02:29:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.45681720925495e-05 | lossAlign: 0
+2025-09-23 02:29:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.898239083355293e-05 | lossAlign: 0
+2025-09-23 02:29:09 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.212831143173389e-05 | lossAlign: 0
+2025-09-23 02:29:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0012434272794052958 | lossAlign: 0
+2025-09-23 02:29:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8347241823212244e-05 | lossAlign: 0
+2025-09-23 02:29:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001092130085453391 | lossAlign: 0
+2025-09-23 02:29:16 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9548193197115324e-05 | lossAlign: 0
+2025-09-23 02:29:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00013549518189392984 | lossAlign: 0
+2025-09-23 02:29:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0019044935470446944 | lossAlign: 0
+2025-09-23 02:29:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.796687840600498e-05 | lossAlign: 0
+2025-09-23 02:29:23 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2870757927885279e-05 | lossAlign: 0
+2025-09-23 02:29:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.812298589560669e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.435409159166738e-05 | lossAlign: 0
+2025-09-23 02:29:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010101318184752017 | lossAlign: 0
+2025-09-23 02:29:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2611618533119326e-06 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.545658521237783e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.227963886980433e-05 | lossAlign: 0
+2025-09-23 02:29:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7465242965263315e-05 | lossAlign: 0
+2025-09-23 02:29:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.759834938449785e-05 | lossAlign: 0
+2025-09-23 02:29:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0485224013100378e-05 | lossAlign: 0
+2025-09-23 02:29:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00032067776191979647 | lossAlign: 0
+2025-09-23 02:29:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.529959111707285e-05 | lossAlign: 0
+2025-09-23 02:29:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010197030496783555 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0013229800388216972 | lossAlign: 0
+2025-09-23 02:29:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.466490983963013e-05 | lossAlign: 0
+2025-09-23 02:29:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018111476674675941 | lossAlign: 0
+2025-09-23 02:29:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00047152003389783204 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8668380309682107e-06 | lossAlign: 0
+2025-09-23 02:29:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8109487427864224e-05 | lossAlign: 0
+2025-09-23 02:29:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.6019125622697175e-06 | lossAlign: 0
+2025-09-23 02:29:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.156561772106215e-06 | lossAlign: 0
+2025-09-23 02:30:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.759352229186334e-06 | lossAlign: 0
+2025-09-23 02:30:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.526615157374181e-05 | lossAlign: 0
+2025-09-23 02:30:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0016307480400428176 | lossAlign: 0
+2025-09-23 02:30:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.652647137641907e-05 | lossAlign: 0
+2025-09-23 02:30:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.051254240446724e-05 | lossAlign: 0
+2025-09-23 02:30:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009408112382516265 | lossAlign: 0
+2025-09-23 02:30:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.813796401023865e-06 | lossAlign: 0
+2025-09-23 02:30:13 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011022052785847336 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.15003387388424e-06 | lossAlign: 0
+2025-09-23 02:30:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011756674211937934 | lossAlign: 0
+2025-09-23 02:30:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000521704088896513 | lossAlign: 0
+2025-09-23 02:30:20 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.063690994371427e-06 | lossAlign: 0
+2025-09-23 02:30:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.24069957161555e-06 | lossAlign: 0
+2025-09-23 02:30:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0989418771932833e-05 | lossAlign: 0
+2025-09-23 02:30:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00019985251128673553 | lossAlign: 0
+2025-09-23 02:30:27 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.85668268892914e-05 | lossAlign: 0
+2025-09-23 02:30:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001837185409385711 | lossAlign: 0
+2025-09-23 02:30:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.7863937652437016e-05 | lossAlign: 0
+2025-09-23 02:30:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6355514844690333e-06 | lossAlign: 0
+2025-09-23 02:30:34 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0005336807807907462 | lossAlign: 0
+2025-09-23 02:30:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8439595805830322e-06 | lossAlign: 0
+2025-09-23 02:30:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.1603982430824544e-06 | lossAlign: 0
+2025-09-23 02:30:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.9148101020837203e-05 | lossAlign: 0
+2025-09-23 02:30:41 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.144119313627016e-06 | lossAlign: 0
+2025-09-23 02:30:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001582096447236836 | lossAlign: 0
+2025-09-23 02:30:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015740694652777165 | lossAlign: 0
+2025-09-23 02:30:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010316848783986643 | lossAlign: 0
+2025-09-23 02:30:48 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.621285527013242e-05 | lossAlign: 0
+2025-09-23 02:30:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.519390106201172e-05 | lossAlign: 0
+2025-09-23 02:30:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.761081855685916e-06 | lossAlign: 0
+2025-09-23 02:30:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011871149763464928 | lossAlign: 0
+2025-09-23 02:30:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.149895489215851e-05 | lossAlign: 0
+2025-09-23 02:31:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.69089183449978e-06 | lossAlign: 0
+2025-09-23 02:31:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014696897414978594 | lossAlign: 0
+2025-09-23 02:31:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.191874414682388e-05 | lossAlign: 0
+2025-09-23 02:31:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010381578613305464 | lossAlign: 0
+2025-09-23 02:31:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0006716384086757898 | lossAlign: 0
+2025-09-23 02:31:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.765632623573765e-05 | lossAlign: 0
+2025-09-23 02:31:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015051252557896078 | lossAlign: 0
+2025-09-23 02:31:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9358263671165332e-05 | lossAlign: 0
+2025-09-23 02:31:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.1580926588503644e-05 | lossAlign: 0
+2025-09-23 02:31:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.539627171761822e-06 | lossAlign: 0
+2025-09-23 02:31:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.214193904772401e-05 | lossAlign: 0
+2025-09-23 02:31:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.325993359088898e-06 | lossAlign: 0
+2025-09-23 02:31:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015496737614739686 | lossAlign: 0
+2025-09-23 02:31:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.100799560546875e-05 | lossAlign: 0
+2025-09-23 02:31:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.981397432857193e-05 | lossAlign: 0
+2025-09-23 02:31:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.397878314601257e-05 | lossAlign: 0
+2025-09-23 02:31:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014638996799476445 | lossAlign: 0
+2025-09-23 02:31:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.891429752111435e-05 | lossAlign: 0
+2025-09-23 02:31:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.18376032737433e-06 | lossAlign: 0
+2025-09-23 02:31:31 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9675209841807373e-05 | lossAlign: 0
+2025-09-23 02:31:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.576284739712719e-05 | lossAlign: 0
+2025-09-23 02:31:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.101112320611719e-05 | lossAlign: 0
+2025-09-23 02:31:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00015482120215892792 | lossAlign: 0
+2025-09-23 02:31:38 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003485189808998257 | lossAlign: 0
+2025-09-23 02:31:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0010299066780135036 | lossAlign: 0
+2025-09-23 02:31:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1807732082379516e-06 | lossAlign: 0
+2025-09-23 02:31:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.188342023146106e-06 | lossAlign: 0
+2025-09-23 02:31:45 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.469206826091977e-06 | lossAlign: 0
+2025-09-23 02:31:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.233101546764374e-06 | lossAlign: 0
+2025-09-23 02:31:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.325626544712577e-05 | lossAlign: 0
+2025-09-23 02:31:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.237434601847781e-06 | lossAlign: 0
+2025-09-23 02:31:52 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3403476259554736e-05 | lossAlign: 0
+2025-09-23 02:31:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2663332856609486e-05 | lossAlign: 0
+2025-09-23 02:31:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001000146585283801 | lossAlign: 0
+2025-09-23 02:31:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4834633222781122e-05 | lossAlign: 0
+2025-09-23 02:31:59 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002656392753124237 | lossAlign: 0
+2025-09-23 02:32:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0011864370899274945 | lossAlign: 0
+2025-09-23 02:32:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.6034145776065998e-05 | lossAlign: 0
+2025-09-23 02:32:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00012894943938590586 | lossAlign: 0
+2025-09-23 02:32:06 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008180169970728457 | lossAlign: 0
+2025-09-23 02:32:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.863906956918072e-06 | lossAlign: 0
+2025-09-23 02:32:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.264946129405871e-06 | lossAlign: 0
+2025-09-23 02:32:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2940748749533668e-05 | lossAlign: 0
+2025-09-23 02:32:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.063606411364162e-06 | lossAlign: 0
+2025-09-23 02:32:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8768732843454927e-05 | lossAlign: 0
+2025-09-23 02:32:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0930356438620947e-05 | lossAlign: 0
+2025-09-23 02:32:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004504118114709854 | lossAlign: 0
+2025-09-23 02:32:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002475864312145859 | lossAlign: 0
+2025-09-23 02:32:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018477534467820078 | lossAlign: 0
+2025-09-23 02:32:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.375317702302709e-05 | lossAlign: 0
+2025-09-23 02:32:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000147913524415344 | lossAlign: 0
+2025-09-23 02:32:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.8313174905415508e-06 | lossAlign: 0
+2025-09-23 02:32:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1538458895520307e-05 | lossAlign: 0
+2025-09-23 02:32:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00031563214724883437 | lossAlign: 0
+2025-09-23 02:32:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010269146878272295 | lossAlign: 0
+2025-09-23 02:32:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6277745089610107e-05 | lossAlign: 0
+2025-09-23 02:32:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0008188930805772543 | lossAlign: 0
+2025-09-23 02:32:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0991281669703312e-05 | lossAlign: 0
+2025-09-23 02:32:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.001008355407975614 | lossAlign: 0
+2025-09-23 02:32:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.376555681228638e-06 | lossAlign: 0
+2025-09-23 02:32:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011364650708856061 | lossAlign: 0
+2025-09-23 02:32:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.808174930483801e-06 | lossAlign: 0
+2025-09-23 02:32:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.330204683355987e-05 | lossAlign: 0
+2025-09-23 02:32:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00017580075655132532 | lossAlign: 0
+2025-09-23 02:32:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3291366940393345e-06 | lossAlign: 0
+2025-09-23 02:32:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.732248584739864e-05 | lossAlign: 0
+2025-09-23 02:32:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.898307765368372e-05 | lossAlign: 0
+2025-09-23 02:32:56 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7372389265801758e-05 | lossAlign: 0
+2025-09-23 02:33:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.000360651349183172 | lossAlign: 0
+2025-09-23 02:33:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.9855901781702414e-05 | lossAlign: 0
+2025-09-23 02:33:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.851359411375597e-05 | lossAlign: 0
+2025-09-23 02:33:03 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.2074049411457963e-05 | lossAlign: 0
+2025-09-23 02:33:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0002400186931481585 | lossAlign: 0
+2025-09-23 02:33:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5010833749329322e-06 | lossAlign: 0
+2025-09-23 02:33:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.01231833267957e-05 | lossAlign: 0
+2025-09-23 02:33:10 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018277975323144346 | lossAlign: 0
+2025-09-23 02:33:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.183766112779267e-06 | lossAlign: 0
+2025-09-23 02:33:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.821517912503623e-06 | lossAlign: 0
+2025-09-23 02:33:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8641205062740482e-05 | lossAlign: 0
+2025-09-23 02:33:17 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.59682526323013e-05 | lossAlign: 0
+2025-09-23 02:33:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.788620445760898e-06 | lossAlign: 0
+2025-09-23 02:33:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4395665150223067e-06 | lossAlign: 0
+2025-09-23 02:33:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5803134121815674e-05 | lossAlign: 0
+2025-09-23 02:33:24 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010069858399219811 | lossAlign: 0
+2025-09-23 02:33:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.288650416128803e-06 | lossAlign: 0
+2025-09-23 02:33:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.78082898654975e-05 | lossAlign: 0
+2025-09-23 02:33:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.655171404825523e-05 | lossAlign: 0
+2025-09-23 02:33:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.639801879122388e-06 | lossAlign: 0
+2025-09-23 02:33:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.824969487846829e-05 | lossAlign: 0
+2025-09-23 02:33:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.0252456781454384e-05 | lossAlign: 0
+2025-09-23 02:33:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9064025309489807e-06 | lossAlign: 0
+2025-09-23 02:33:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016354105900973082 | lossAlign: 0
+2025-09-23 02:33:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.733065230131615e-05 | lossAlign: 0
+2025-09-23 02:33:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.53547899168916e-05 | lossAlign: 0
+2025-09-23 02:33:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.1407528038253076e-05 | lossAlign: 0
+2025-09-23 02:33:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1518478459038306e-05 | lossAlign: 0
+2025-09-23 02:33:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.9632802731357515e-06 | lossAlign: 0
+2025-09-23 02:33:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0007217891979962587 | lossAlign: 0
+2025-09-23 02:33:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0003451766970101744 | lossAlign: 0
+2025-09-23 02:33:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.6783883842872456e-05 | lossAlign: 0
+2025-09-23 02:34:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00014159340935293585 | lossAlign: 0
+2025-09-23 02:34:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.392128959007096e-06 | lossAlign: 0
+2025-09-23 02:34:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.9533808932174e-05 | lossAlign: 0
+2025-09-23 02:34:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2879259884357452e-05 | lossAlign: 0
+2025-09-23 02:34:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00030885491287335753 | lossAlign: 0
+2025-09-23 02:34:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.304068513898528e-06 | lossAlign: 0
+2025-09-23 02:34:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5536332032061182e-05 | lossAlign: 0
+2025-09-23 02:34:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0002316230384167e-05 | lossAlign: 0
+2025-09-23 02:34:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.802444444365392e-06 | lossAlign: 0
+2025-09-23 02:34:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3696479729551356e-06 | lossAlign: 0
+2025-09-23 02:34:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.9282687288941815e-05 | lossAlign: 0
+2025-09-23 02:34:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7089155992143787e-05 | lossAlign: 0
+2025-09-23 02:34:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00027496719849295914 | lossAlign: 0
+2025-09-23 02:34:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.3737668016110547e-05 | lossAlign: 0
+2025-09-23 02:34:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.367210436204914e-05 | lossAlign: 0
+2025-09-23 02:34:21 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.5353781438752776e-06 | lossAlign: 0
+2025-09-23 02:34:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003371774684637785 | lossAlign: 0
+2025-09-23 02:34:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00016233138740062714 | lossAlign: 0
+2025-09-23 02:34:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.190200691780774e-06 | lossAlign: 0
+2025-09-23 02:34:28 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.005187166621909e-06 | lossAlign: 0
+2025-09-23 02:34:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.181167802627897e-07 | lossAlign: 0
+2025-09-23 02:34:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.340143171546515e-06 | lossAlign: 0
+2025-09-23 02:34:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00020949957252014428 | lossAlign: 0
+2025-09-23 02:34:35 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.58607280254364e-06 | lossAlign: 0
+2025-09-23 02:34:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.003451885189861059 | lossAlign: 0
+2025-09-23 02:34:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.521571099758148e-06 | lossAlign: 0
+2025-09-23 02:34:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.004953608382493e-05 | lossAlign: 0
+2025-09-23 02:34:42 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3711929568671621e-05 | lossAlign: 0
+2025-09-23 02:34:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.326489478349686e-05 | lossAlign: 0
+2025-09-23 02:34:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.179599803435849e-05 | lossAlign: 0
+2025-09-23 02:34:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.416753992903978e-06 | lossAlign: 0
+2025-09-23 02:34:49 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.470754407113418e-05 | lossAlign: 0
+2025-09-23 02:34:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.881291897618212e-05 | lossAlign: 0
+2025-09-23 02:34:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.324569691671059e-05 | lossAlign: 0
+2025-09-23 02:34:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004320375737734139 | lossAlign: 0
+2025-09-23 02:34:57 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.296040060580708e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.293593757320195e-05 | lossAlign: 0
+2025-09-23 02:35:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.7844786270870827e-05 | lossAlign: 0
+2025-09-23 02:35:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0025442992337048054 | lossAlign: 0
+2025-09-23 02:35:04 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.012871355982497e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0435104741191026e-05 | lossAlign: 0
+2025-09-23 02:35:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.8153881430625916e-05 | lossAlign: 0
+2025-09-23 02:35:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.978398242703406e-06 | lossAlign: 0
+2025-09-23 02:35:11 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00022151778102852404 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.38046839690287e-07 | lossAlign: 0
+2025-09-23 02:35:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011447940050857142 | lossAlign: 0
+2025-09-23 02:35:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.079802501015365e-05 | lossAlign: 0
+2025-09-23 02:35:18 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.0155906895524822e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.004811981692910194 | lossAlign: 0
+2025-09-23 02:35:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.7841992050525732e-05 | lossAlign: 0
+2025-09-23 02:35:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.892118396237493e-05 | lossAlign: 0
+2025-09-23 02:35:25 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00011419699876569211 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0009111137478612363 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.290156423143344e-06 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.1128525733947754e-05 | lossAlign: 0
+2025-09-23 02:35:32 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.244702358846553e-05 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00039347526035271585 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.650044722140592e-07 | lossAlign: 0
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+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00018955506675411016 | lossAlign: 0
+2025-09-23 02:35:39 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.9411290092393756e-05 | lossAlign: 0
+2025-09-23 02:35:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5341598555096425e-05 | lossAlign: 0
+2025-09-23 02:35:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.057385275606066e-05 | lossAlign: 0
+2025-09-23 02:35:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 4.8815272748470306e-05 | lossAlign: 0
+2025-09-23 02:35:46 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.639993024582509e-05 | lossAlign: 0
+2025-09-23 02:35:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.064569672365906e-06 | lossAlign: 0
+2025-09-23 02:35:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 8.979812264442444e-06 | lossAlign: 0
+2025-09-23 02:35:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.00010284973541274667 | lossAlign: 0
+2025-09-23 02:35:53 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6399255400756374e-05 | lossAlign: 0
+2025-09-23 02:36:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.3197898624639492e-05 | lossAlign: 0
+2025-09-23 02:36:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.716926873195916e-05 | lossAlign: 0
+2025-09-23 02:36:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 9.905724255077075e-06 | lossAlign: 0
+2025-09-23 02:36:00 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 2.4876853785826825e-06 | lossAlign: 0
+2025-09-23 02:36:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0004881687054876238 | lossAlign: 0
+2025-09-23 02:36:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.0001510184520157054 | lossAlign: 0
+2025-09-23 02:36:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 3.622637905209558e-06 | lossAlign: 0
+2025-09-23 02:36:07 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 5.0541832024464384e-05 | lossAlign: 0
+2025-09-23 02:36:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 6.504174962174147e-05 | lossAlign: 0
+2025-09-23 02:36:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.092858868418261e-05 | lossAlign: 0
+2025-09-23 02:36:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.027924872934818268 | lossAlign: 0
+2025-09-23 02:36:14 | INFO | LVLM-Med | Loss: 
+ 	 temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 7.539514626841992e-06 | lossAlign: 0
+2025-09-23 02:37:26 | WARNING | wandb | message_loop has been closed