whisper-NST-cons2e5
This model is a fine-tuned version of openai/whisper-small on the NBAILAB/NST - NO-CLOSE dataset. It achieves the following results on the evaluation set:
- Loss: 0.3521
- Wer: 11.8586
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: 2e-05
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2517 | 0.1 | 1000 | 0.4131 | 18.4721 |
| 0.1931 | 0.2 | 2000 | 0.3531 | 19.0422 |
| 0.1598 | 0.3 | 3000 | 0.3605 | 16.8757 |
| 0.1541 | 0.4 | 4000 | 0.3367 | 14.4812 |
| 0.1443 | 0.5 | 5000 | 0.3274 | 13.3409 |
| 0.1301 | 0.6 | 6000 | 0.3481 | 10.7184 |
| 0.1266 | 0.7 | 7000 | 0.3452 | 12.9989 |
| 0.1216 | 0.8 | 8000 | 0.3215 | 10.8324 |
| 0.1121 | 0.9 | 9000 | 0.3160 | 11.5165 |
| 0.1171 | 1.0 | 10000 | 0.3521 | 11.8586 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1