whisper-base-aug-20-april-lightning-v1
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: 0.1044
- Wer: 85.2539
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.5768 | 1.0 | 1424 | 0.2062 | 98.4412 |
| 0.1775 | 2.0 | 2848 | 0.1505 | 89.7549 |
| 0.1321 | 3.0 | 4272 | 0.1304 | 86.5233 |
| 0.109 | 4.0 | 5696 | 0.1184 | 87.7905 |
| 0.0935 | 5.0 | 7120 | 0.1108 | 83.8661 |
| 0.0815 | 6.0 | 8544 | 0.1072 | 85.3635 |
| 0.0722 | 7.0 | 9968 | 0.1058 | 84.4405 |
| 0.0644 | 8.0 | 11392 | 0.1049 | 82.3862 |
| 0.0575 | 9.0 | 12816 | 0.1049 | 84.2761 |
| 0.0521 | 9.9933 | 14230 | 0.1044 | 85.2539 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.2.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1