---
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: 0.1146
- Wer: 0.2395

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 6.2283        | 1.0     | 313  | 0.1208          | 0.2747 |
| 5.6174        | 2.0     | 626  | 0.1240          | 0.2641 |
| 4.1014        | 3.0     | 939  | 0.1180          | 0.2639 |
| 3.4699        | 4.0     | 1252 | 0.1206          | 0.2272 |
| 2.8022        | 5.0     | 1565 | 0.1198          | 0.2375 |
| 2.371         | 6.0     | 1878 | 0.1143          | 0.2325 |
| 2.1677        | 7.0     | 2191 | 0.1143          | 0.2337 |
| 1.9842        | 8.0     | 2504 | 0.1135          | 0.2305 |
| 1.787         | 9.0     | 2817 | 0.1124          | 0.2352 |
| 1.6133        | 10.0    | 3130 | 0.1123          | 0.2277 |
| 1.5033        | 11.0    | 3443 | 0.1119          | 0.2283 |
| 1.4237        | 12.0    | 3756 | 0.1115          | 0.2246 |
| 1.3321        | 13.0    | 4069 | 0.1115          | 0.2247 |
| 1.2518        | 14.0    | 4382 | 0.1113          | 0.2247 |
| 1.2225        | 14.9536 | 4680 | 0.1112          | 0.2275 |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0