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whisper-tiny-minds14
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7473
- Wer Ortho: 0.2788
- Wer: 0.2834
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: 3.220378398329722e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9850038588304092,0.9902432649395926) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 205
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| No log | 1.0 | 28 | 2.9124 | 0.5305 | 0.3991 |
| No log | 2.0 | 56 | 1.3721 | 0.4516 | 0.4091 |
| No log | 3.0 | 84 | 0.6397 | 0.3856 | 0.3872 |
| No log | 4.0 | 112 | 0.5424 | 0.3849 | 0.3819 |
| No log | 5.0 | 140 | 0.5124 | 0.4460 | 0.4410 |
| No log | 6.0 | 168 | 0.5153 | 0.3479 | 0.3477 |
| No log | 7.0 | 196 | 0.5565 | 0.3418 | 0.3424 |
| No log | 8.0 | 224 | 0.5882 | 0.3208 | 0.3229 |
| No log | 9.0 | 252 | 0.6248 | 0.3356 | 0.3371 |
| No log | 10.0 | 280 | 0.6545 | 0.3282 | 0.3300 |
| No log | 11.0 | 308 | 0.7122 | 0.3060 | 0.3093 |
| No log | 12.0 | 336 | 0.7473 | 0.2788 | 0.2834 |
| No log | 13.0 | 364 | 0.7717 | 0.3072 | 0.3093 |
| No log | 14.0 | 392 | 0.7852 | 0.3424 | 0.3447 |
| No log | 15.0 | 420 | 0.8127 | 0.3307 | 0.3318 |
| No log | 16.0 | 448 | 0.8471 | 0.3300 | 0.3294 |
| No log | 17.0 | 476 | 0.8614 | 0.3405 | 0.3406 |
| 0.4338 | 18.0 | 504 | 0.8992 | 0.3627 | 0.3630 |
| 0.4338 | 19.0 | 532 | 0.9157 | 0.3640 | 0.3648 |
| 0.4338 | 20.0 | 560 | 0.9274 | 0.3578 | 0.3589 |
| 0.4338 | 21.0 | 588 | 0.9275 | 0.3387 | 0.3377 |
| 0.4338 | 22.0 | 616 | 0.9371 | 0.3381 | 0.3371 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1
- Datasets 2.13.2.dev1
- Tokenizers 0.13.3
