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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: 0.0060
- Wer: 0.0688
- Cer: 0.0280
## 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0058 | 1.0 | 157 | 0.0056 | 0.0608 | 0.0253 |
| 0.0052 | 2.0 | 314 | 0.0055 | 0.0583 | 0.0240 |
| 0.0037 | 3.0 | 471 | 0.0054 | 0.0586 | 0.0247 |
| 0.0032 | 4.0 | 628 | 0.0054 | 0.0615 | 0.0242 |
| 0.0038 | 5.0 | 785 | 0.0056 | 0.0581 | 0.0235 |
| 0.0015 | 6.0 | 942 | 0.0058 | 0.0610 | 0.0245 |
| 0.0023 | 7.0 | 1099 | 0.0062 | 0.0612 | 0.0245 |
| 0.0014 | 8.0 | 1256 | 0.0066 | 0.0639 | 0.0251 |
| 0.0013 | 9.0 | 1413 | 0.0070 | 0.0693 | 0.0361 |
| 0.0007 | 10.0 | 1570 | 0.0074 | 0.0671 | 0.0349 |
| 0.0006 | 11.0 | 1727 | 0.0078 | 0.0695 | 0.0363 |
| 0.0002 | 12.0 | 1884 | 0.0082 | 0.0733 | 0.0387 |
| 0.0001 | 13.0 | 2041 | 0.0084 | 0.0710 | 0.0374 |
| 0.0001 | 14.0 | 2198 | 0.0086 | 0.0688 | 0.0452 |
| 0.0002 | 15.0 | 2355 | 0.0088 | 0.0706 | 0.0454 |
| 0.0001 | 16.0 | 2512 | 0.0089 | 0.0717 | 0.0455 |
| 0.0001 | 17.0 | 2669 | 0.0090 | 0.0711 | 0.0455 |
| 0.0001 | 18.0 | 2826 | 0.0090 | 0.0711 | 0.0361 |
| 0.0 | 19.0 | 2983 | 0.0098 | 0.0870 | 0.0457 |
| 0.0001 | 19.8768 | 3120 | 0.0091 | 0.0706 | 0.0362 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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