Whisper tiny AR - BH
This model is a fine-tuned version of openai/whisper-tiny on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:
- Loss: 0.0081
- Wer: 0.0885
- Cer: 0.0350
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
0.007 | 1.0 | 469 | 0.0069 | 0.0927 | 0.0352 |
0.0076 | 2.0 | 938 | 0.0065 | 0.0919 | 0.0353 |
0.0036 | 3.0 | 1407 | 0.0065 | 0.0905 | 0.0350 |
0.0041 | 4.0 | 1876 | 0.0068 | 0.0887 | 0.0340 |
0.003 | 5.0 | 2345 | 0.0071 | 0.0876 | 0.0330 |
0.003 | 6.0 | 2814 | 0.0076 | 0.0900 | 0.0358 |
0.0024 | 7.0 | 3283 | 0.0080 | 0.0916 | 0.0349 |
0.002 | 8.0 | 3752 | 0.0086 | 0.0889 | 0.0329 |
0.0015 | 9.0 | 4221 | 0.0089 | 0.1674 | 0.0708 |
0.0003 | 10.0 | 4690 | 0.0094 | 0.1690 | 0.0731 |
0.0005 | 11.0 | 5159 | 0.0097 | 0.1658 | 0.0705 |
0.0009 | 12.0 | 5628 | 0.0099 | 0.1669 | 0.0714 |
0.0005 | 13.0 | 6097 | 0.0101 | 0.1672 | 0.0712 |
0.0004 | 14.0 | 6566 | 0.0118 | 0.1017 | 0.0411 |
0.0001 | 15.0 | 7035 | 0.0103 | 0.1660 | 0.0713 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-tiny