---
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: 0.1077
- Wer: 0.2309

## 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: 8
- total_train_batch_size: 64
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 3.3412        | 1.0     | 157  | 0.1041          | 0.2149 |
| 3.0121        | 2.0     | 314  | 0.1054          | 0.2123 |
| 2.6811        | 3.0     | 471  | 0.1033          | 0.2079 |
| 2.2468        | 4.0     | 628  | 0.1062          | 0.2163 |
| 2.1438        | 5.0     | 785  | 0.1029          | 0.2168 |
| 1.8098        | 6.0     | 942  | 0.1035          | 0.2131 |
| 1.7488        | 7.0     | 1099 | 0.1023          | 0.2190 |
| 1.52          | 8.0     | 1256 | 0.1020          | 0.2116 |
| 1.431         | 9.0     | 1413 | 0.1013          | 0.2112 |
| 1.3151        | 10.0    | 1570 | 0.1005          | 0.2168 |
| 1.2219        | 11.0    | 1727 | 0.1011          | 0.2107 |
| 1.1879        | 12.0    | 1884 | 0.1003          | 0.2097 |
| 1.1158        | 13.0    | 2041 | 0.1007          | 0.2098 |
| 1.0995        | 14.0    | 2198 | 0.0998          | 0.2095 |
| 1.0596        | 14.9088 | 2340 | 0.1001          | 0.2107 |


### Framework versions

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