Whisper Base French
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_11_0 fr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4968
- Wer on
mozilla-foundation/common_voice_11_0fr: 24.0648 - Wer on
google/fleursfr_fr: 24.20 - Wer on
facebook/voxpopulifr: 23.66
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: 32
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.534 | 0.2 | 1000 | 0.5710 | 27.4408 |
| 0.4409 | 1.2 | 2000 | 0.5279 | 25.1981 |
| 0.3095 | 2.2 | 3000 | 0.5117 | 25.0818 |
| 0.3285 | 3.2 | 4000 | 0.4995 | 24.0601 |
| 0.3032 | 4.2 | 5000 | 0.4968 | 24.0648 |
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-base-french-cased
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 frtest set self-reported24.065
- Wer on google/fleurs fr_frtest set self-reported24.200
- Wer on facebook/voxpopuli frtest set self-reported23.660