Whisper Small Ha - Eldad Akhaumere
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 4.9575
- Wer Ortho: 110.3468
- Wer: 108.1055
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: 0.0005
- 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
- num_epochs: 13.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.5785 | 3.1847 | 500 | 3.8839 | 99.5593 | 99.8438 |
| 1.1623 | 6.3694 | 1000 | 4.4847 | 97.7582 | 98.0078 |
| 0.9893 | 9.5541 | 1500 | 4.7922 | 108.7373 | 107.6172 |
| 0.8816 | 12.7389 | 2000 | 4.9575 | 110.3468 | 108.1055 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for eldad-akhaumere/whisper-small-ha-v9
Base model
openai/whisper-small