Whisper Base French
This model is a fine-tuned version of qanastek/whisper-base-french-cased on the google/fleurs fr_fr dataset. It achieves the following results on the evaluation set:
- Loss: 0.5402
- Wer: 23.7955
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-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.3835 | 105.26 | 1000 | 0.5892 | 25.4237 |
| 0.2837 | 210.53 | 2000 | 0.5526 | 23.8955 |
| 0.2323 | 315.79 | 3000 | 0.5432 | 24.0122 |
| 0.1961 | 421.05 | 4000 | 0.5402 | 23.7955 |
| 0.1863 | 526.32 | 5000 | 0.5395 | 23.7955 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0