openai/whisper-small
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: 0.9750
- Wer: 21.3693
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3559 | 0.1 | 1000 | 0.9147 | 29.3252 |
| 0.3154 | 0.2 | 2000 | 1.1353 | 26.5718 |
| 0.359 | 0.3 | 3000 | 0.9208 | 25.3987 |
| 0.273 | 0.4 | 4000 | 0.9591 | 24.3877 |
| 0.2326 | 0.5 | 5000 | 0.9207 | 21.9052 |
| 0.2992 | 1.04 | 6000 | 0.9445 | 22.4556 |
| 0.2265 | 1.14 | 7000 | 0.9660 | 21.2230 |
| 0.2059 | 1.24 | 8000 | 0.9785 | 20.9551 |
| 0.2239 | 1.34 | 9000 | 0.9637 | 21.6300 |
| 0.2163 | 1.44 | 10000 | 0.9750 | 21.3693 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2