./hamsa-v0.6Q
This model is a fine-tuned version of openai/whisper-medium on the nadsoft/arabic-98 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2781
- Wer: 23.4124
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9225 | 0.33 | 100 | 0.8743 | 24.5136 |
| 0.2721 | 0.67 | 200 | 0.2782 | 24.1367 |
| 0.2474 | 1.0 | 300 | 0.2781 | 23.4124 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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