---
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 - BA
  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 - BA

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: 0.0875
- Wer: 0.1939

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.9262        | 1.0     | 469  | 0.0907          | 0.1917 |
| 1.8739        | 2.0     | 938  | 0.0907          | 0.1874 |
| 1.4395        | 3.0     | 1407 | 0.0898          | 0.1991 |
| 1.3835        | 4.0     | 1876 | 0.0880          | 0.2003 |
| 1.1837        | 5.0     | 2345 | 0.0884          | 0.2065 |
| 1.0963        | 6.0     | 2814 | 0.0870          | 0.2020 |
| 1.0446        | 7.0     | 3283 | 0.0877          | 0.1967 |
| 0.8945        | 8.0     | 3752 | 0.0867          | 0.1895 |
| 0.8261        | 9.0     | 4221 | 0.0858          | 0.1986 |
| 0.7863        | 10.0    | 4690 | 0.0849          | 0.1889 |
| 0.7641        | 11.0    | 5159 | 0.0854          | 0.1932 |
| 0.6898        | 12.0    | 5628 | 0.0853          | 0.1910 |
| 0.6968        | 13.0    | 6097 | 0.0845          | 0.1914 |
| 0.6905        | 14.0    | 6566 | 0.0846          | 0.1914 |
| 0.6316        | 14.9685 | 7020 | 0.0846          | 0.1858 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1