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openai/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: 0.3834
- Wer: 11.8889
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: 16
- eval_batch_size: 32
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5582 | 0.12 | 500 | 0.3660 | 14.8170 |
| 0.2285 | 1.02 | 1000 | 0.2919 | 12.6304 |
| 0.2038 | 1.15 | 1500 | 0.2795 | 11.3850 |
| 0.074 | 2.04 | 2000 | 0.3150 | 12.1043 |
| 0.2165 | 2.17 | 2500 | 0.2978 | 12.8510 |
| 0.0399 | 3.07 | 3000 | 0.3467 | 11.7322 |
| 0.045 | 3.19 | 3500 | 0.3501 | 11.7218 |
| 0.0187 | 4.09 | 4000 | 0.3834 | 11.8889 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
