Whisper Medium Arabic - Mostafa Khedr
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2691
- Wer: 38.0222
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2453 | 0.4156 | 1000 | 0.3289 | 42.9602 |
0.2326 | 0.8313 | 2000 | 0.2976 | 42.0990 |
0.139 | 1.2469 | 3000 | 0.2883 | 41.0376 |
0.1081 | 1.6625 | 4000 | 0.2720 | 39.0763 |
0.0543 | 2.0781 | 5000 | 0.2691 | 38.0222 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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openai/whisper-medium