---
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: 0.0892
- Wer: 0.1918

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.406         | 1.0   | 625  | 0.0887          | 0.1907 |
| 1.3322        | 2.0   | 1250 | 0.0906          | 0.1874 |
| 1.2587        | 3.0   | 1875 | 0.0903          | 0.1844 |
| 1.1135        | 4.0   | 2500 | 0.0892          | 0.1954 |
| 1.0444        | 5.0   | 3125 | 0.0879          | 0.1883 |
| 0.9344        | 6.0   | 3750 | 0.0867          | 0.1802 |
| 0.9135        | 7.0   | 4375 | 0.0874          | 0.1854 |
| 0.8567        | 8.0   | 5000 | 0.0861          | 0.1882 |
| 0.7738        | 9.0   | 5625 | 0.0857          | 0.1951 |
| 0.7419        | 10.0  | 6250 | 0.0852          | 0.1958 |
| 0.7167        | 11.0  | 6875 | 0.0854          | 0.1933 |
| 0.6929        | 12.0  | 7500 | 0.0850          | 0.1874 |
| 0.6539        | 13.0  | 8125 | 0.0847          | 0.1908 |
| 0.6448        | 14.0  | 8750 | 0.0845          | 0.1883 |
| 0.5887        | 15.0  | 9375 | 0.0846          | 0.1892 |


### Framework versions

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