Whisper Small french - RF
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7760
- Wer: 49.2308
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: 10
- training_steps: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.4424 | 5.0 | 10 | 3.5394 | 57.6923 |
| 1.7535 | 10.0 | 20 | 1.9843 | 54.6154 |
| 0.7841 | 15.0 | 30 | 1.2915 | 45.3846 |
| 0.2479 | 20.0 | 40 | 0.9029 | 48.4615 |
| 0.1579 | 25.0 | 50 | 0.7760 | 49.2308 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-tiny