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: 0.4429
- Wer: 52.7568
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3629 | 1.03 | 1000 | 0.4917 | 53.1291 |
| 0.289 | 2.06 | 2000 | 0.4747 | 61.3855 |
| 0.2996 | 3.08 | 3000 | 0.4542 | 55.4692 |
| 0.2331 | 4.11 | 4000 | 0.4353 | 51.4917 |
| 0.1566 | 5.14 | 5000 | 0.4429 | 52.7568 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2