Whisper Small ar1 - Mohamed Shaaban
This model is a fine-tuned version of openai/whisper-base on the Common standard ar Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4585
- Wer: 65.2720
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 |
|---|---|---|---|---|
| 0.444 | 0.42 | 1000 | 0.5684 | 73.7587 |
| 0.4161 | 0.83 | 2000 | 0.4995 | 68.0147 |
| 0.3282 | 1.25 | 3000 | 0.4841 | 68.92 |
| 0.2915 | 1.66 | 4000 | 0.4663 | 67.6120 |
| 0.2639 | 2.08 | 5000 | 0.4585 | 65.2720 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Mohamedshaaban2001/MSDC-whisper-base
Base model
openai/whisper-baseDataset used to train Mohamedshaaban2001/MSDC-whisper-base
Evaluation results
- Wer on Common standard ar Voice 11.0self-reported65.272