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: 0.1802
- Wer: 6.9921
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 |
|---|---|---|---|---|
| 0.4228 | 0.38 | 30 | 0.2223 | 8.7717 |
| 0.1719 | 0.75 | 60 | 0.1884 | 7.3780 |
| 0.1354 | 1.12 | 90 | 0.1769 | 7.1890 |
| 0.0727 | 1.5 | 120 | 0.1763 | 7.5591 |
| 0.0779 | 1.88 | 150 | 0.1691 | 6.5512 |
| 0.0468 | 2.25 | 180 | 0.1698 | 6.7244 |
| 0.0316 | 2.62 | 210 | 0.1678 | 6.3386 |
| 0.0316 | 3.0 | 240 | 0.1663 | 6.4488 |
| 0.0151 | 3.38 | 270 | 0.1770 | 8.3307 |
| 0.0143 | 3.75 | 300 | 0.1724 | 9.1024 |
| 0.0119 | 4.12 | 330 | 0.1743 | 6.9528 |
| 0.0072 | 4.5 | 360 | 0.1788 | 6.9134 |
| 0.0069 | 4.88 | 390 | 0.1802 | 6.9921 |
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