Whisper Large V2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3167
- Wer: 11.6330
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: 3e-05
- train_batch_size: 16
- 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: 20
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6772 | 0.71 | 30 | 0.3209 | 16.8396 |
| 0.2613 | 1.43 | 60 | 0.3041 | 12.8163 |
| 0.1683 | 2.14 | 90 | 0.2908 | 11.8332 |
| 0.0777 | 2.86 | 120 | 0.2916 | 10.8138 |
| 0.0428 | 3.57 | 150 | 0.2965 | 11.7786 |
| 0.0228 | 4.29 | 180 | 0.3114 | 11.8150 |
| 0.0107 | 5.0 | 210 | 0.3167 | 11.6330 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
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Base model
openai/whisper-large-v2