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whisper-small-nya
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: 0.5086
- Wer: 27.5487
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: 2.5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.2671 | 0.99 | 500 | 0.5633 | 35.9244 |
| 0.1372 | 1.97 | 1000 | 0.4515 | 48.1630 |
| 0.0742 | 2.96 | 1500 | 0.4474 | 32.4985 |
| 0.0341 | 3.94 | 2000 | 0.4595 | 35.3574 |
| 0.0191 | 4.93 | 2500 | 0.4722 | 28.2930 |
| 0.0073 | 5.92 | 3000 | 0.4774 | 25.3633 |
| 0.0031 | 6.9 | 3500 | 0.4875 | 25.9539 |
| 0.0009 | 7.89 | 4000 | 0.4995 | 26.2611 |
| 0.0012 | 8.87 | 4500 | 0.5056 | 25.1861 |
| 0.0004 | 9.86 | 5000 | 0.5086 | 27.5487 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
