---
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: 0.0037
- Wer: 0.0571
- Cer: 0.0223

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0078        | 1.0     | 282  | 0.0037          | 0.0529 | 0.0209 |
| 0.0047        | 2.0     | 564  | 0.0040          | 0.0550 | 0.0208 |
| 0.0018        | 3.0     | 846  | 0.0050          | 0.0646 | 0.0261 |
| 0.0013        | 4.0     | 1128 | 0.0053          | 0.0594 | 0.0224 |
| 0.0009        | 5.0     | 1410 | 0.0062          | 0.0659 | 0.0241 |
| 0.0008        | 6.0     | 1692 | 0.0066          | 0.0659 | 0.0257 |
| 0.0008        | 7.0     | 1974 | 0.0068          | 0.0626 | 0.0243 |
| 0.0006        | 8.0     | 2256 | 0.0072          | 0.0615 | 0.0223 |
| 0.0006        | 9.0     | 2538 | 0.0075          | 0.0668 | 0.0256 |
| 0.0003        | 10.0    | 2820 | 0.0077          | 0.0643 | 0.0238 |
| 0.0003        | 11.0    | 3102 | 0.0082          | 0.0577 | 0.0211 |
| 0.0002        | 12.0    | 3384 | 0.0090          | 0.0643 | 0.0237 |
| 0.0002        | 13.0    | 3666 | 0.0100          | 0.0637 | 0.0222 |
| 0.0001        | 14.0    | 3948 | 0.0100          | 0.0615 | 0.0229 |
| 0.0001        | 15.0    | 4230 | 0.0104          | 0.0603 | 0.0232 |
| 0.0001        | 16.0    | 4512 | 0.0111          | 0.0606 | 0.0216 |
| 0.0001        | 17.0    | 4794 | 0.0115          | 0.0614 | 0.0211 |
| 0.0           | 18.0    | 5076 | 0.0115          | 0.0570 | 0.0196 |
| 0.0           | 19.0    | 5358 | 0.0121          | 0.0614 | 0.0225 |
| 0.0           | 20.0    | 5640 | 0.0119          | 0.0595 | 0.0219 |
| 0.0           | 21.0    | 5922 | 0.0121          | 0.0588 | 0.0209 |
| 0.0           | 22.0    | 6204 | 0.0121          | 0.0597 | 0.0215 |
| 0.0           | 23.0    | 6486 | 0.0121          | 0.0601 | 0.0215 |
| 0.0           | 24.0    | 6768 | 0.0126          | 0.0609 | 0.0234 |
| 0.0           | 24.9130 | 7025 | 0.0121          | 0.0588 | 0.0204 |


### Framework versions

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