Whisper Large French Cased
This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_11_0 fr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2962
- Wer: 11.9100
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: 4
- eval_batch_size: 2
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3357 | 0.2 | 1000 | 0.3994 | 16.1523 |
| 0.3026 | 0.4 | 2000 | 0.3802 | 15.2403 |
| 0.2904 | 0.6 | 3000 | 0.3389 | 14.0045 |
| 0.2407 | 0.8 | 4000 | 0.3135 | 12.7947 |
| 0.2451 | 1.0 | 5000 | 0.2962 | 11.9100 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Dataset used to train qanastek/whisper-large-french-cased
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 frtest set self-reported11.910