Whisper Medium with 1000 orders SSD superU
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.0551
- Wer: 114.5969
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: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.3178 | 0.3831 | 100 | 3.1949 | 211.3345 |
| 2.5484 | 0.7663 | 200 | 2.3725 | 319.0767 |
| 2.0593 | 1.1494 | 300 | 2.2722 | 248.3126 |
| 2.0603 | 1.5326 | 400 | 2.2479 | 253.4519 |
| 2.0258 | 1.9157 | 500 | 2.2259 | 302.7082 |
| 1.6141 | 2.2989 | 600 | 2.2450 | 191.7982 |
| 1.729 | 2.6820 | 700 | 2.2441 | 221.9182 |
| 1.4741 | 3.0651 | 800 | 2.3114 | 169.6906 |
| 1.351 | 3.4483 | 900 | 2.3248 | 199.7299 |
| 1.4636 | 3.8314 | 1000 | 2.3174 | 177.5240 |
| 1.1092 | 4.2146 | 1100 | 2.4755 | 143.9276 |
| 1.0713 | 4.5977 | 1200 | 2.4954 | 122.6198 |
| 1.0927 | 4.9808 | 1300 | 2.4714 | 153.5291 |
| 0.7693 | 5.3640 | 1400 | 2.6916 | 124.3843 |
| 0.7594 | 5.7471 | 1500 | 2.7017 | 125.2438 |
| 0.576 | 6.1303 | 1600 | 2.8599 | 117.2104 |
| 0.5304 | 6.5134 | 1700 | 2.9010 | 120.1431 |
| 0.508 | 6.8966 | 1800 | 2.9175 | 120.5536 |
| 0.3794 | 7.2797 | 1900 | 3.0556 | 111.9378 |
| 0.3816 | 7.6628 | 2000 | 3.0551 | 114.5969 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.2.2+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3