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: 0.0180
- Wer: 2.0030
- Cer: 1.0182
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: 4
- total_train_batch_size: 64
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0211 | 1.0 | 469 | 0.0229 | 2.6548 | 1.3564 |
| 0.0192 | 2.0 | 938 | 0.0209 | 2.1622 | 1.1267 |
| 0.0149 | 3.0 | 1407 | 0.0193 | 1.3596 | 0.6720 |
| 0.0145 | 4.0 | 1876 | 0.0182 | 1.1658 | 0.6142 |
| 0.0106 | 5.0 | 2345 | 0.0176 | 1.7265 | 0.9079 |
| 0.0121 | 6.0 | 2814 | 0.0171 | 1.5142 | 0.7794 |
| 0.0139 | 7.0 | 3283 | 0.0168 | 1.6885 | 0.8300 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0