openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the pphuc25/FranceMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.5011
- Wer: 37.2434
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: 0.0001
- train_batch_size: 8
- 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: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0211 | 1.0 | 215 | 0.9633 | 38.9296 |
| 0.5896 | 2.0 | 430 | 1.0086 | 52.6393 |
| 0.3027 | 3.0 | 645 | 1.1072 | 38.9296 |
| 0.1371 | 4.0 | 860 | 1.2011 | 38.7097 |
| 0.1004 | 5.0 | 1075 | 1.2837 | 41.9355 |
| 0.0638 | 6.0 | 1290 | 1.3137 | 41.4223 |
| 0.0513 | 7.0 | 1505 | 1.3113 | 38.6364 |
| 0.0374 | 8.0 | 1720 | 1.3284 | 39.0029 |
| 0.0279 | 9.0 | 1935 | 1.4303 | 39.3695 |
| 0.0176 | 10.0 | 2150 | 1.4479 | 37.9765 |
| 0.0144 | 11.0 | 2365 | 1.4417 | 39.0029 |
| 0.0173 | 12.0 | 2580 | 1.4390 | 38.9296 |
| 0.0036 | 13.0 | 2795 | 1.4696 | 40.0293 |
| 0.0053 | 14.0 | 3010 | 1.4461 | 38.8563 |
| 0.0039 | 15.0 | 3225 | 1.4651 | 37.6100 |
| 0.0026 | 16.0 | 3440 | 1.4707 | 35.9971 |
| 0.0018 | 17.0 | 3655 | 1.4972 | 37.6833 |
| 0.0003 | 18.0 | 3870 | 1.4943 | 37.5367 |
| 0.0002 | 19.0 | 4085 | 1.4995 | 37.2434 |
| 0.0002 | 20.0 | 4300 | 1.5011 | 37.2434 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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