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: 0.3142
- Wer: 9.6853
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 |
|---|---|---|---|---|
| 0.2948 | 0.12 | 500 | 0.2476 | 9.9138 |
| 0.1795 | 1.08 | 1000 | 0.2286 | 10.1859 |
| 0.0625 | 2.04 | 1500 | 0.2518 | 9.6295 |
| 0.0834 | 2.16 | 2000 | 0.2286 | 9.9808 |
| 0.0202 | 3.12 | 2500 | 0.2667 | 9.4985 |
| 0.0067 | 4.07 | 3000 | 0.2954 | 9.7513 |
| 0.0151 | 5.03 | 3500 | 0.3155 | 9.6539 |
| 0.0048 | 5.15 | 4000 | 0.3142 | 9.6853 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2