Whisper-medium-BTC
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: 0.3882
- Wer: 6.6247
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: 4e-07
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 350
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8163 | 1.01 | 25 | 0.8356 | 10.0635 |
| 0.7916 | 2.02 | 50 | 0.8102 | 9.7351 |
| 0.7563 | 3.03 | 75 | 0.7621 | 9.5088 |
| 0.7154 | 4.05 | 100 | 0.7107 | 9.2337 |
| 0.6548 | 5.06 | 125 | 0.6589 | 9.3801 |
| 0.6017 | 7.01 | 150 | 0.6062 | 9.0074 |
| 0.5333 | 8.02 | 175 | 0.5347 | 8.6214 |
| 0.4493 | 9.03 | 200 | 0.4738 | 8.2842 |
| 0.4016 | 10.04 | 225 | 0.4333 | 7.1172 |
| 0.3738 | 11.05 | 250 | 0.4057 | 6.7001 |
| 0.3544 | 13.01 | 275 | 0.3882 | 6.6247 |
| 0.3294 | 14.02 | 300 | 0.3764 | 6.6957 |
| 0.313 | 15.03 | 325 | 0.3692 | 6.6602 |
| 0.3023 | 16.04 | 350 | 0.3668 | 6.6468 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2