metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny AR - BH
results: []
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: 0.0095
- Wer: 0.1037
- Cer: 0.0382
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 |
|---|---|---|---|---|---|
| 0.0104 | 1.0 | 407 | 0.0098 | 0.1182 | 0.0449 |
| 0.0068 | 2.0 | 814 | 0.0088 | 0.1055 | 0.0373 |
| 0.0075 | 3.0 | 1221 | 0.0088 | 0.1008 | 0.0356 |
| 0.0057 | 4.0 | 1628 | 0.0091 | 0.0992 | 0.0345 |
| 0.0047 | 5.0 | 2035 | 0.0097 | 0.0997 | 0.0349 |
| 0.0038 | 6.0 | 2442 | 0.0103 | 0.0994 | 0.0340 |
| 0.0024 | 7.0 | 2849 | 0.0109 | 0.1033 | 0.0357 |
| 0.0031 | 8.0 | 3256 | 0.0113 | 0.1015 | 0.0351 |
| 0.0014 | 9.0 | 3663 | 0.0118 | 0.1003 | 0.0350 |
| 0.0018 | 10.0 | 4070 | 0.0123 | 0.1014 | 0.0349 |
| 0.0013 | 11.0 | 4477 | 0.0128 | 0.1122 | 0.0405 |
| 0.0011 | 12.0 | 4884 | 0.0130 | 0.1037 | 0.0379 |
| 0.0004 | 13.0 | 5291 | 0.0132 | 0.1032 | 0.0379 |
| 0.0019 | 14.0 | 5698 | 0.0141 | 0.1055 | 0.0397 |
| 0.001 | 14.9643 | 6090 | 0.0135 | 0.1017 | 0.0371 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0