---
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: 0.1029
- Wer: 0.2133

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 2.6022        | 1.0     | 154  | 0.0981          | 0.2051 |
| 2.386         | 2.0     | 308  | 0.0994          | 0.2067 |
| 1.9412        | 3.0     | 462  | 0.0996          | 0.2022 |
| 1.824         | 4.0     | 616  | 0.0998          | 0.2045 |
| 1.6295        | 5.0     | 770  | 0.0976          | 0.2101 |
| 1.458         | 6.0     | 924  | 0.0982          | 0.2007 |
| 1.2992        | 7.0     | 1078 | 0.0959          | 0.2063 |
| 1.1839        | 8.0     | 1232 | 0.0971          | 0.2088 |
| 1.0944        | 9.0     | 1386 | 0.0954          | 0.2085 |
| 1.032         | 10.0    | 1540 | 0.0956          | 0.2104 |
| 0.9384        | 11.0    | 1694 | 0.0948          | 0.2026 |
| 0.8799        | 12.0    | 1848 | 0.0942          | 0.2053 |
| 0.8374        | 13.0    | 2002 | 0.0939          | 0.2062 |
| 0.7891        | 14.0    | 2156 | 0.0940          | 0.2065 |
| 0.7622        | 14.9070 | 2295 | 0.0940          | 0.2050 |


### Framework versions

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