Instructions to use mohmdsh/whisper-with-augmentation-small-arabic_with-diacritics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohmdsh/whisper-with-augmentation-small-arabic_with-diacritics with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohmdsh/whisper-with-augmentation-small-arabic_with-diacritics")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohmdsh/whisper-with-augmentation-small-arabic_with-diacritics") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohmdsh/whisper-with-augmentation-small-arabic_with-diacritics") - Notebooks
- Google Colab
- Kaggle
whisper-with-augmentation-small-arabic_with-diacritics
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7564
- Wer: 0.7171
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0489 | 3.5133 | 200 | 0.7624 | 0.7171 |
| 0.0143 | 7.0177 | 400 | 1.0633 | 0.7185 |
| 0.005 | 10.5310 | 600 | 1.0752 | 0.7178 |
| 0.0017 | 14.0354 | 800 | 1.1699 | 0.7127 |
| 0.0009 | 17.5487 | 1000 | 1.1766 | 0.7163 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for mohmdsh/whisper-with-augmentation-small-arabic_with-diacritics
Base model
openai/whisper-small