whisper-small-mupe-3
This model is a fine-tuned version of lejonck/whisper-small-mupe-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7351
- Wer: 0.2430
- Cer: 0.5095
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: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.2677 | 1.0 | 1000 | 0.4901 | 0.2760 | 0.5167 |
| 0.1301 | 2.0 | 2000 | 0.5221 | 0.2478 | 0.5118 |
| 0.0496 | 3.0 | 3000 | 0.5680 | 0.2489 | 0.5119 |
| 0.0204 | 4.0 | 4000 | 0.6225 | 0.2662 | 0.5170 |
| 0.0103 | 5.0 | 5000 | 0.6579 | 0.2456 | 0.5110 |
| 0.0091 | 6.0 | 6000 | 0.6706 | 0.2502 | 0.5122 |
| 0.0012 | 7.0 | 7000 | 0.6920 | 0.2427 | 0.5111 |
| 0.0005 | 8.0 | 8000 | 0.7184 | 0.2422 | 0.5098 |
| 0.0003 | 9.0 | 9000 | 0.7554 | 0.2417 | 0.5112 |
| 0.0003 | 10.0 | 10000 | 0.7458 | 0.2478 | 0.5122 |
| 0.0002 | 11.0 | 11000 | 0.7628 | 0.2523 | 0.5121 |
| 0.0002 | 12.0 | 12000 | 0.7785 | 0.2453 | 0.5119 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.7.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4