whisper-small-sq
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2403
- Wer: 0.2590
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: 8
- 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: 8000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3334 | 0.27 | 1000 | 0.3662 | 0.4138 |
| 0.2593 | 0.53 | 2000 | 0.3056 | 0.3329 |
| 0.2297 | 0.8 | 3000 | 0.2799 | 0.3052 |
| 0.1687 | 1.06 | 4000 | 0.2627 | 0.2798 |
| 0.1664 | 1.33 | 5000 | 0.2524 | 0.2724 |
| 0.1578 | 1.59 | 6000 | 0.2453 | 0.2652 |
| 0.1543 | 1.86 | 7000 | 0.2407 | 0.2626 |
| 0.1209 | 2.13 | 8000 | 0.2403 | 0.2590 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.2.0.dev20230923
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
openai/whisper-small