WhisperATCSmall
This model is a fine-tuned version of openai/whisper-small on the ATC lmejiasSydney dataset. It achieves the following results on the evaluation set:
- Loss: 8.2932
- Wer Ortho: 76.8786
- Wer: 77.1429
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| No log | 10.0 | 10 | 2.4187 | 111.5607 | 105.7143 |
| No log | 20.0 | 20 | 2.4427 | 71.0983 | 71.4286 |
| 1.3246 | 30.0 | 30 | 2.9333 | 82.6590 | 82.8571 |
| 1.3246 | 40.0 | 40 | 2.3413 | 79.7688 | 79.4286 |
| 0.0534 | 50.0 | 50 | 2.7293 | 194.7977 | 193.1429 |
| 0.0534 | 60.0 | 60 | 3.9019 | 89.0173 | 89.1429 |
| 0.0534 | 70.0 | 70 | 5.5183 | 79.7688 | 80.0 |
| 0.0119 | 80.0 | 80 | 6.4220 | 323.6994 | 321.7143 |
| 0.0119 | 90.0 | 90 | 5.2189 | 654.9133 | 646.8571 |
| 0.0614 | 100.0 | 100 | 7.4941 | 435.2601 | 430.2857 |
| 0.0614 | 110.0 | 110 | 7.0980 | 82.0809 | 82.2857 |
| 0.0614 | 120.0 | 120 | 6.3404 | 204.0462 | 202.8571 |
| 0.0 | 130.0 | 130 | 7.3077 | 98.8439 | 98.8571 |
| 0.0 | 140.0 | 140 | 7.1859 | 83.2370 | 83.4286 |
| 0.0 | 150.0 | 150 | 7.1508 | 85.5491 | 85.7143 |
| 0.0 | 160.0 | 160 | 6.9526 | 79.1908 | 79.4286 |
| 0.0 | 170.0 | 170 | 6.8956 | 84.9711 | 85.1429 |
| 0.0 | 180.0 | 180 | 6.8715 | 79.7688 | 80.0 |
| 0.0 | 190.0 | 190 | 7.1711 | 83.2370 | 83.4286 |
| 0.0 | 200.0 | 200 | 7.2134 | 83.2370 | 83.4286 |
| 0.0 | 210.0 | 210 | 7.2450 | 84.9711 | 85.1429 |
| 0.0 | 220.0 | 220 | 7.2228 | 83.2370 | 83.4286 |
| 0.0 | 230.0 | 230 | 7.2169 | 80.3468 | 80.5714 |
| 0.0 | 240.0 | 240 | 7.3043 | 78.0347 | 78.2857 |
| 0.0 | 250.0 | 250 | 7.4497 | 80.9249 | 81.1429 |
| 0.0 | 260.0 | 260 | 7.6275 | 79.7688 | 80.0 |
| 0.0 | 270.0 | 270 | 7.4590 | 80.3468 | 80.5714 |
| 0.0 | 280.0 | 280 | 7.3765 | 80.3468 | 80.5714 |
| 0.0 | 290.0 | 290 | 7.1675 | 76.8786 | 77.1429 |
| 0.0 | 300.0 | 300 | 7.1708 | 78.6127 | 78.8571 |
| 0.0 | 310.0 | 310 | 7.2078 | 79.7688 | 80.0 |
| 0.0 | 320.0 | 320 | 7.1781 | 78.6127 | 78.8571 |
| 0.0 | 330.0 | 330 | 7.3729 | 82.6590 | 82.8571 |
| 0.0 | 340.0 | 340 | 7.9443 | 83.8150 | 84.0 |
| 0.0 | 350.0 | 350 | 7.7305 | 83.8150 | 84.0 |
| 0.0 | 360.0 | 360 | 7.7460 | 84.3931 | 84.5714 |
| 0.0 | 370.0 | 370 | 7.4392 | 86.1272 | 86.2857 |
| 0.0 | 380.0 | 380 | 7.4408 | 81.5029 | 81.7143 |
| 0.0 | 390.0 | 390 | 7.2765 | 84.3931 | 84.5714 |
| 0.0 | 400.0 | 400 | 7.7561 | 82.0809 | 82.2857 |
| 0.0 | 410.0 | 410 | 7.1968 | 82.0809 | 82.2857 |
| 0.0 | 420.0 | 420 | 7.1473 | 80.9249 | 81.1429 |
| 0.0 | 430.0 | 430 | 7.2199 | 81.5029 | 81.7143 |
| 0.0 | 440.0 | 440 | 7.3039 | 79.1908 | 79.4286 |
| 0.0 | 450.0 | 450 | 7.3708 | 75.1445 | 75.4286 |
| 0.0 | 460.0 | 460 | 8.0785 | 79.1908 | 79.4286 |
| 0.0 | 470.0 | 470 | 8.3612 | 74.5665 | 74.8571 |
| 0.0 | 480.0 | 480 | 8.4102 | 77.4566 | 77.7143 |
| 0.0 | 490.0 | 490 | 8.3026 | 74.5665 | 74.8571 |
| 0.0 | 500.0 | 500 | 8.2932 | 76.8786 | 77.1429 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.21.0