whisper-tiny-aug-7-may-lightning-v1
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1300
- Wer: 86.2590
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: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0747 | 1.0 | 712 | 0.4463 | 102.0236 |
| 0.3496 | 2.0 | 1424 | 0.2607 | 98.4686 |
| 0.2411 | 3.0 | 2136 | 0.2071 | 92.8878 |
| 0.1966 | 4.0 | 2848 | 0.1819 | 94.1085 |
| 0.1699 | 5.0 | 3560 | 0.1653 | 92.2555 |
| 0.1514 | 6.0 | 4272 | 0.1533 | 88.5561 |
| 0.1377 | 7.0 | 4984 | 0.1452 | 88.0289 |
| 0.1265 | 8.0 | 5696 | 0.1391 | 86.8913 |
| 0.117 | 9.0 | 6408 | 0.1331 | 87.4382 |
| 0.1089 | 10.0 | 7120 | 0.1300 | 86.2590 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.1
- Tokenizers 0.21.1