whisper-medium-atcosim
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0493
- Wer: 79.0563
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.129 | 8.33 | 500 | 0.0419 | 2.3014 |
| 0.0004 | 16.67 | 1000 | 0.0428 | 17.1282 |
| 0.0002 | 25.0 | 1500 | 0.0426 | 10.4510 |
| 0.0012 | 33.33 | 2000 | 0.0427 | 39.6277 |
| 0.0003 | 41.67 | 2500 | 0.0423 | 58.2515 |
| 0.0 | 50.0 | 3000 | 0.0456 | 54.7324 |
| 0.0 | 58.33 | 3500 | 0.0468 | 61.8402 |
| 0.0 | 66.67 | 4000 | 0.0477 | 68.6794 |
| 0.0 | 75.0 | 4500 | 0.0483 | 72.7172 |
| 0.0 | 83.33 | 5000 | 0.0488 | 76.2502 |
| 0.0 | 91.67 | 5500 | 0.0491 | 78.2228 |
| 0.0 | 100.0 | 6000 | 0.0493 | 79.0563 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0