whisper-base
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1952
- Wer: 10.4439
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: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 60000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2139 | 0.0833 | 5000 | 0.1884 | 16.6399 |
| 0.1146 | 0.1667 | 10000 | 0.1447 | 13.0148 |
| 0.0686 | 0.25 | 15000 | 0.1384 | 11.3586 |
| 0.0427 | 0.3333 | 20000 | 0.1471 | 11.4970 |
| 0.0274 | 0.4167 | 25000 | 0.1585 | 10.8926 |
| 0.0195 | 0.5 | 30000 | 0.1702 | 11.3447 |
| 0.0155 | 0.5833 | 35000 | 0.1773 | 10.6100 |
| 0.0126 | 1.0062 | 40000 | 0.1863 | 11.4255 |
| 0.0099 | 1.0895 | 45000 | 0.1929 | 10.6665 |
| 0.01 | 1.1729 | 50000 | 0.1933 | 10.6665 |
| 0.0085 | 1.2562 | 55000 | 0.1953 | 10.5224 |
| 0.0085 | 1.3395 | 60000 | 0.1952 | 10.4439 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3