---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper base 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 base AR - BH

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0124
- Wer: 11.8561
- Cer: 3.6023

## 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: 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: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Cer    | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:------:|:---------------:|:-------:|
| 0.0124        | 0.2895 | 800   | 6.9720 | 0.0166          | 21.3510 |
| 0.0076        | 0.5790 | 1600  | 4.4857 | 0.0124          | 14.3371 |
| 0.0042        | 0.8685 | 2400  | 4.2342 | 0.0112          | 13.1816 |
| 0.0053        | 1.1581 | 3200  | 4.8224 | 0.0133          | 14.4143 |
| 0.0041        | 1.4476 | 4000  | 4.0206 | 0.0121          | 12.9768 |
| 0.0023        | 1.7371 | 4800  | 3.7118 | 0.0116          | 11.9643 |
| 0.0022        | 2.0268 | 5600  | 4.0467 | 0.0125          | 12.7101 |
| 0.002         | 2.3163 | 6400  | 3.7803 | 0.0125          | 12.1962 |
| 0.0016        | 2.6058 | 7200  | 3.7763 | 0.0124          | 12.2696 |
| 0.0018        | 2.8952 | 8000  | 3.6627 | 0.0122          | 12.0570 |
| 0.0013        | 3.1849 | 8800  | 0.0126 | 12.0957         | 3.6893  |
| 0.0015        | 3.4744 | 9600  | 0.0126 | 12.2232         | 3.6893  |
| 0.0013        | 3.7639 | 10400 | 0.0124 | 11.8561         | 3.6023  |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0