| --- |
| license: apache-2.0 |
| datasets: |
| - stanfordnlp/sst2 |
| - nyu-mll/glue |
| language: |
| - en |
| metrics: |
| - accuracy |
| - f1 |
| --- |
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| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
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| # distilbert-base-uncased-finetuned-emotion |
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| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2150 |
| - Accuracy: 0.9255 |
| - F1: 0.9256 |
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|
| ## Model description |
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| More information needed |
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| ## Intended uses & limitations |
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| More information needed |
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| ## Training and evaluation data |
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| More information needed |
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| ## Training procedure |
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| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
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| ### Training results |
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| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.8042 | 1.0 | 250 | 0.3079 | 0.9075 | 0.9068 | |
| | 0.2448 | 2.0 | 500 | 0.2150 | 0.9255 | 0.9256 | |
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| ### Framework versions |
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| - Transformers 4.41.0 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
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