Whisper small withaq - T5SA
This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 - Arabic dataset. It achieves the following results on the evaluation set:
- Loss: 1.6060
- Wer: 64.0180
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: 6
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0051 | 22.22 | 1000 | 1.3485 | 66.5792 |
| 0.0003 | 44.44 | 2000 | 1.5180 | 62.4313 |
| 0.0002 | 66.67 | 3000 | 1.5829 | 63.3683 |
| 0.0001 | 88.89 | 4000 | 1.6060 | 64.0180 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.1
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Model tree for naiftamia/whisper-small-Withaq
Base model
openai/whisper-base