Egyptian Whisper Small
This model is a fine-tuned version of openai/whisper-small on the Egyptian-ASR-MGB-3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9939
- Wer: 46.2893
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4615 | 6.8966 | 100 | 0.6496 | 48.0162 |
0.072 | 13.7931 | 200 | 0.7459 | 46.3990 |
0.0122 | 20.6897 | 300 | 0.8380 | 45.6863 |
0.0054 | 27.5862 | 400 | 0.8981 | 45.0764 |
0.0033 | 34.4828 | 500 | 0.9322 | 45.2820 |
0.0025 | 41.3793 | 600 | 0.9555 | 45.4670 |
0.002 | 48.2759 | 700 | 0.9724 | 46.1454 |
0.0017 | 55.1724 | 800 | 0.9843 | 45.9467 |
0.0016 | 62.0690 | 900 | 0.9916 | 46.0769 |
0.0015 | 68.9655 | 1000 | 0.9939 | 46.2893 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small