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---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper tiny AR - BH
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0408
- Wer: 0.3145
- Cer: 0.1128
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.1136 | 1.0 | 94 | 0.0777 | 5.3133 | 1.8561 |
| 0.0458 | 2.0 | 188 | 0.0478 | 2.6311 | 1.1803 |
| 0.0292 | 3.0 | 282 | 0.0402 | 1.8776 | 0.9786 |
| 0.0239 | 4.0 | 376 | 0.0369 | 0.9783 | 0.4714 |
| 0.0182 | 5.0 | 470 | 0.0368 | 0.6109 | 0.2680 |
| 0.0163 | 6.0 | 564 | 0.0357 | 0.6387 | 0.2671 |
| 0.0132 | 7.0 | 658 | 0.0363 | 0.3701 | 0.1281 |
| 0.01 | 8.0 | 752 | 0.0369 | 0.5068 | 0.1884 |
| 0.0067 | 9.0 | 846 | 0.0392 | 0.3609 | 0.1184 |
| 0.0056 | 10.0 | 940 | 0.0354 | 0.3155 | 0.1000 |
| 0.0041 | 11.0 | 1034 | 0.0382 | 0.3131 | 0.0964 |
| 0.0027 | 12.0 | 1128 | 0.0363 | 0.3419 | 0.1087 |
| 0.0018 | 13.0 | 1222 | 0.0387 | 0.3640 | 0.1111 |
| 0.0015 | 14.0 | 1316 | 0.0388 | 0.3428 | 0.1179 |
| 0.0012 | 15.0 | 1410 | 0.0382 | 0.3730 | 0.1359 |
| 0.0012 | 16.0 | 1504 | 0.0386 | 0.2863 | 0.0933 |
| 0.0007 | 17.0 | 1598 | 0.0387 | 0.3721 | 0.1560 |
| 0.0005 | 18.0 | 1692 | 0.0391 | 0.2780 | 0.0847 |
| 0.0004 | 19.0 | 1786 | 0.0405 | 0.2985 | 0.1114 |
| 0.0003 | 20.0 | 1880 | 0.0409 | 0.3452 | 0.1222 |
| 0.0002 | 21.0 | 1974 | 0.0405 | 0.3475 | 0.1441 |
| 0.0 | 22.0 | 2068 | 0.0413 | 0.2614 | 0.0754 |
| 0.0 | 23.0 | 2162 | 0.0423 | 0.3339 | 0.1156 |
| 0.0 | 24.0 | 2256 | 0.0426 | 0.2676 | 0.0854 |
| 0.0 | 25.0 | 2350 | 0.0442 | 0.3357 | 0.1101 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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