whisper-small-santali-sanlish-frozen
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8507
- Wer: 45.2756
- Cer: 13.0534
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 240
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 5.6601 | 1.0 | 97 | 3.5435 | 88.8780 | 50.1312 |
| 1.9323 | 2.0 | 194 | 1.0238 | 63.3858 | 20.8749 |
| 0.7640 | 3.0 | 291 | 0.8547 | 56.5945 | 16.8854 |
| 0.5141 | 4.0 | 388 | 0.7974 | 49.4094 | 14.4882 |
| 0.3704 | 5.0 | 485 | 0.7753 | 48.1299 | 14.4882 |
| 0.2677 | 6.0 | 582 | 0.7642 | 46.5551 | 13.2633 |
| 0.1872 | 7.0 | 679 | 0.7691 | 52.9528 | 21.5398 |
| 0.1286 | 8.0 | 776 | 0.7709 | 47.3425 | 13.2283 |
| 0.0885 | 9.0 | 873 | 0.7775 | 45.4724 | 13.0184 |
| 0.0601 | 10.0 | 970 | 0.7860 | 52.8543 | 29.1514 |
| 0.0410 | 11.0 | 1067 | 0.7939 | 45.0787 | 12.6684 |
| 0.0292 | 12.0 | 1164 | 0.8127 | 45.3740 | 12.6509 |
| 0.0199 | 13.0 | 1261 | 0.8140 | 44.9803 | 13.0709 |
| 0.0148 | 14.0 | 1358 | 0.8224 | 44.4882 | 12.8784 |
| 0.0115 | 15.0 | 1455 | 0.8331 | 45.3740 | 13.0009 |
| 0.0098 | 16.0 | 1552 | 0.8363 | 56.2008 | 21.9598 |
| 0.0082 | 17.0 | 1649 | 0.8423 | 45.0787 | 13.0009 |
| 0.0072 | 18.0 | 1746 | 0.8474 | 56.1024 | 22.0472 |
| 0.0064 | 19.0 | 1843 | 0.8507 | 45.2756 | 13.0534 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.23.1