Whisper Small Ori vi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3950
- Wer: 17.6577
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 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: 200
- training_steps: 1300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1125 | 0.0667 | 30 | 0.9877 | 30.4667 |
| 0.9337 | 0.1333 | 60 | 0.7582 | 18.3338 |
| 0.7185 | 0.2 | 90 | 0.4716 | 16.3129 |
| 0.493 | 0.2667 | 120 | 0.4382 | 16.1893 |
| 0.4328 | 0.3333 | 150 | 0.4298 | 15.6223 |
| 0.4127 | 0.4 | 180 | 0.4208 | 16.8726 |
| 0.3865 | 0.4667 | 210 | 0.4171 | 20.0422 |
| 0.419 | 0.5333 | 240 | 0.4141 | 17.0835 |
| 0.4141 | 0.6 | 270 | 0.4157 | 15.8258 |
| 0.464 | 0.6667 | 300 | 0.4077 | 16.9235 |
| 0.4303 | 0.7333 | 330 | 0.4043 | 18.4865 |
| 0.4418 | 0.8 | 360 | 0.4050 | 16.7999 |
| 0.4786 | 0.8667 | 390 | 0.3981 | 15.1352 |
| 0.4238 | 0.9333 | 420 | 0.3953 | 17.0907 |
| 0.3986 | 1.0 | 450 | 0.3926 | 16.7054 |
| 0.2304 | 1.0667 | 480 | 0.3948 | 16.3928 |
| 0.2583 | 1.1333 | 510 | 0.3943 | 16.6327 |
| 0.2385 | 1.2 | 540 | 0.3997 | 15.1425 |
| 0.2126 | 1.2667 | 570 | 0.3985 | 15.0552 |
| 0.2259 | 1.3333 | 600 | 0.3970 | 16.5964 |
| 0.2237 | 1.4 | 630 | 0.3964 | 16.5382 |
| 0.2344 | 1.4667 | 660 | 0.3983 | 17.9485 |
| 0.2068 | 1.5333 | 690 | 0.3974 | 17.9703 |
| 0.2535 | 1.6 | 720 | 0.3950 | 17.6577 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0