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: 0.2953
- Wer: 11.3276
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: 12
- 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 |
|---|---|---|---|---|
| 0.5452 | 0.4839 | 15 | 0.3714 | 23.2724 |
| 0.2911 | 0.9677 | 30 | 0.2866 | 18.6494 |
| 0.1304 | 1.4516 | 45 | 0.2713 | 13.6270 |
| 0.1196 | 1.9355 | 60 | 0.2595 | 12.7436 |
| 0.0595 | 2.4194 | 75 | 0.2615 | 11.8964 |
| 0.043 | 2.9032 | 90 | 0.2700 | 13.0098 |
| 0.0229 | 3.3871 | 105 | 0.2854 | 15.4786 |
| 0.0176 | 3.8710 | 120 | 0.2747 | 12.9856 |
| 0.0101 | 4.3548 | 135 | 0.2882 | 11.1340 |
| 0.0069 | 4.8387 | 150 | 0.2953 | 11.3276 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v2