openai/whisper-medium.en
This model is a fine-tuned version of openai/whisper-medium.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5812
- Wer: 11.9424
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: 32
- 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 |
|---|---|---|---|---|
| 0.3378 | 1.01 | 500 | 0.3505 | 12.4476 |
| 0.1075 | 2.02 | 1000 | 0.3609 | 11.8145 |
| 0.041 | 3.03 | 1500 | 0.4061 | 11.6578 |
| 0.0256 | 4.04 | 2000 | 0.4597 | 11.8066 |
| 0.0099 | 5.06 | 2500 | 0.5020 | 12.0964 |
| 0.0028 | 6.07 | 3000 | 0.5476 | 11.9816 |
| 0.0015 | 7.08 | 3500 | 0.5869 | 11.7100 |
| 0.0018 | 8.09 | 4000 | 0.5812 | 11.9424 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2