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: 0.0061
- Wer: 0.0763
- Cer: 0.0310
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 |
|---|---|---|---|---|---|
| 0.0046 | 1.0 | 701 | 0.0052 | 0.0782 | 0.0297 |
| 0.0035 | 2.0 | 1402 | 0.0049 | 0.0717 | 0.0281 |
| 0.0036 | 3.0 | 2103 | 0.0052 | 0.0719 | 0.0290 |
| 0.0026 | 4.0 | 2804 | 0.0055 | 0.0671 | 0.0267 |
| 0.0012 | 5.0 | 3505 | 0.0058 | 0.0699 | 0.0275 |
| 0.0017 | 6.0 | 4206 | 0.0062 | 0.0691 | 0.0283 |
| 0.0012 | 7.0 | 4907 | 0.0067 | 0.0710 | 0.0285 |
| 0.0007 | 8.0 | 5608 | 0.0071 | 0.0681 | 0.0273 |
| 0.0005 | 9.0 | 6309 | 0.0075 | 0.0704 | 0.0287 |
| 0.0005 | 10.0 | 7010 | 0.0077 | 0.0695 | 0.0278 |
| 0.0003 | 11.0 | 7711 | 0.0079 | 0.0693 | 0.0270 |
| 0.0001 | 12.0 | 8412 | 0.0080 | 0.0728 | 0.0285 |
| 0.0002 | 13.0 | 9113 | 0.0081 | 0.0738 | 0.0289 |
| 0.0002 | 14.0 | 9814 | 0.0093 | 0.0770 | 0.0318 |
| 0.0001 | 14.9793 | 10500 | 0.0083 | 0.0717 | 0.0284 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0