---
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: 0.1260
- Wer: 0.2865

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 78.8449       | 1.0     | 313  | 0.1892          | 0.7483 |
| 23.7046       | 2.0     | 626  | 0.1465          | 0.4188 |
| 13.1378       | 3.0     | 939  | 0.1347          | 0.3632 |
| 8.2072        | 4.0     | 1252 | 0.1312          | 0.3285 |
| 5.8166        | 5.0     | 1565 | 0.1316          | 0.2937 |
| 4.5461        | 6.0     | 1878 | 0.1339          | 0.2916 |
| 3.8785        | 7.0     | 2191 | 0.1276          | 0.2838 |
| 3.1975        | 8.0     | 2504 | 0.1253          | 0.2762 |
| 2.8784        | 9.0     | 2817 | 0.1240          | 0.2881 |
| 2.6303        | 10.0    | 3130 | 0.1238          | 0.2719 |
| 2.481         | 11.0    | 3443 | 0.1225          | 0.2670 |
| 2.2994        | 12.0    | 3756 | 0.1221          | 0.2641 |
| 2.0863        | 13.0    | 4069 | 0.1214          | 0.2672 |
| 2.0235        | 14.0    | 4382 | 0.1213          | 0.2638 |
| 2.015         | 14.9536 | 4680 | 0.1213          | 0.2626 |


### Framework versions

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