Whisper Tiny French Cased
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_11_0 fr dataset. It achieves the following results on the evaluation set:
- Loss: 0.6509
- Wer on
mozilla-foundation/common_voice_11_0
fr
: 33.0655 - Wer on
google/fleurs
fr_fr
: 36.69 - Wer on
facebook/voxpopuli
fr
: 32.71
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 |
---|---|---|---|---|
0.7185 | 0.2 | 1000 | 0.7608 | 38.1636 |
0.6052 | 1.2 | 2000 | 0.6949 | 34.9513 |
0.4467 | 2.2 | 3000 | 0.6708 | 34.3393 |
0.4773 | 3.2 | 4000 | 0.6536 | 33.2102 |
0.4479 | 4.2 | 5000 | 0.6509 | 33.0655 |
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-tiny-french-cased
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Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 frtest set self-reported33.065
- Wer on google/fleurs fr_frtest set self-reported36.690
- Wer on facebook/voxpopuli frtest set self-reported32.710