Whisper Medium Ar - 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: 0.2694
- Wer: 38.0957
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 |
---|---|---|---|---|
0.2458 | 0.4156 | 1000 | 0.3291 | 42.8960 |
0.2301 | 0.8313 | 2000 | 0.2966 | 42.4461 |
0.1394 | 1.2469 | 3000 | 0.2905 | 41.3148 |
0.108 | 1.6625 | 4000 | 0.2722 | 38.6282 |
0.0534 | 2.0781 | 5000 | 0.2694 | 38.0957 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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