---
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: 0.0034
- Wer: 0.0479
- Cer: 0.0195

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0039        | 1.0   | 215  | 0.0034          | 0.0436 | 0.0167 |
| 0.0028        | 2.0   | 430  | 0.0039          | 0.0525 | 0.0204 |
| 0.0019        | 3.0   | 645  | 0.0051          | 0.0605 | 0.0231 |
| 0.0012        | 4.0   | 860  | 0.0054          | 0.0628 | 0.0232 |
| 0.0008        | 5.0   | 1075 | 0.0057          | 0.0648 | 0.0240 |
| 0.0006        | 6.0   | 1290 | 0.0061          | 0.0597 | 0.0212 |
| 0.0006        | 7.0   | 1505 | 0.0063          | 0.0621 | 0.0252 |
| 0.0004        | 8.0   | 1720 | 0.0073          | 0.0644 | 0.0251 |
| 0.0004        | 9.0   | 1935 | 0.0074          | 0.0621 | 0.0248 |
| 0.0002        | 10.0  | 2150 | 0.0081          | 0.0671 | 0.0253 |
| 0.0004        | 11.0  | 2365 | 0.0080          | 0.0632 | 0.0221 |
| 0.0002        | 12.0  | 2580 | 0.0083          | 0.0565 | 0.0207 |
| 0.0001        | 13.0  | 2795 | 0.0090          | 0.0570 | 0.0201 |
| 0.0001        | 14.0  | 3010 | 0.0105          | 0.0630 | 0.0263 |
| 0.0001        | 15.0  | 3225 | 0.0109          | 0.0608 | 0.0242 |
| 0.0001        | 16.0  | 3440 | 0.0118          | 0.0597 | 0.0221 |
| 0.0           | 17.0  | 3655 | 0.0119          | 0.0595 | 0.0220 |
| 0.0           | 18.0  | 3870 | 0.0130          | 0.0621 | 0.0235 |
| 0.0           | 19.0  | 4085 | 0.0133          | 0.0597 | 0.0231 |
| 0.0           | 20.0  | 4300 | 0.0133          | 0.0592 | 0.0240 |
| 0.0           | 21.0  | 4515 | 0.0135          | 0.0605 | 0.0237 |
| 0.0           | 22.0  | 4730 | 0.0135          | 0.0592 | 0.0231 |
| 0.0           | 23.0  | 4945 | 0.0135          | 0.0592 | 0.0231 |
| 0.0           | 24.0  | 5160 | 0.0124          | 0.0589 | 0.0228 |
| 0.0           | 25.0  | 5375 | 0.0135          | 0.0590 | 0.0231 |


### Framework versions

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