whisper-small-ar
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1581
- Wer Ortho: 27.8630
- Wer: 5.0804
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: 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.7097 | 0.0842 | 50 | 0.5331 | 51.0035 | 11.0584 |
0.3752 | 0.1684 | 100 | 0.3281 | 42.8571 | 8.3150 |
0.221 | 0.2525 | 150 | 0.2201 | 36.9540 | 6.8078 |
0.1948 | 0.3367 | 200 | 0.1996 | 33.5891 | 6.3167 |
0.1947 | 0.4209 | 250 | 0.1833 | 31.1098 | 5.8425 |
0.1708 | 0.5051 | 300 | 0.1752 | 29.3388 | 5.2667 |
0.1667 | 0.5892 | 350 | 0.1680 | 28.5714 | 5.3514 |
0.1606 | 0.6734 | 400 | 0.1631 | 28.8076 | 5.1312 |
0.1525 | 0.7576 | 450 | 0.1600 | 28.6305 | 5.2159 |
0.1513 | 0.8418 | 500 | 0.1581 | 27.8630 | 5.0804 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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