Whisper Small FR - CHARNI Issam
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3304
- Wer: 39.0543
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3517 | 0.23 | 1000 | 0.3930 | 56.0857 |
| 0.2998 | 0.46 | 2000 | 0.3602 | 30.5030 |
| 0.2702 | 0.69 | 3000 | 0.3396 | 41.1543 |
| 0.2603 | 0.91 | 4000 | 0.3304 | 39.0543 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cpu
- Datasets 2.16.1
- Tokenizers 0.15.0
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