Whisper Base Arabic
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 ar dataset. It achieves the following results on the evaluation set:
- Loss: 0.5856
- Wer: 80.4777
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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7392 | 1.53 | 500 | 0.8623 | 100.8133 |
| 0.5938 | 3.07 | 1000 | 0.7397 | 93.6651 |
| 0.5388 | 4.6 | 1500 | 0.6953 | 92.3005 |
| 0.4982 | 6.13 | 2000 | 0.6682 | 88.9392 |
| 0.4795 | 7.67 | 2500 | 0.6512 | 90.1524 |
| 0.4483 | 9.2 | 3000 | 0.6373 | 87.1234 |
| 0.4374 | 10.74 | 3500 | 0.6261 | 85.3144 |
| 0.4331 | 12.27 | 4000 | 0.6179 | 86.4290 |
| 0.4125 | 13.8 | 4500 | 0.6106 | 83.2865 |
| 0.3984 | 15.34 | 5000 | 0.6059 | 83.0676 |
| 0.4035 | 16.87 | 5500 | 0.6008 | 82.2165 |
| 0.3997 | 18.4 | 6000 | 0.5970 | 81.1195 |
| 0.3878 | 19.94 | 6500 | 0.5941 | 81.7153 |
| 0.3827 | 21.47 | 7000 | 0.5906 | 81.2559 |
| 0.3785 | 23.01 | 7500 | 0.5892 | 81.0506 |
| 0.372 | 24.54 | 8000 | 0.5882 | 81.4248 |
| 0.3655 | 26.07 | 8500 | 0.5865 | 81.0479 |
| 0.3697 | 27.61 | 9000 | 0.5856 | 80.4777 |
| 0.3658 | 29.14 | 9500 | 0.5849 | 80.6128 |
| 0.3539 | 30.67 | 10000 | 0.5848 | 80.6696 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0