---
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 - BH
  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 - BH

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: 0.0151
- Wer: 17.8284
- Cer: 5.3577

## 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: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Cer     | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:-------:|:---------------:|:-------:|
| 0.0425        | 0.3011 | 400   | 11.2952 | 0.0330          | 37.6901 |
| 0.0258        | 0.6023 | 800   | 7.9539  | 0.0218          | 25.4742 |
| 0.0197        | 0.9034 | 1200  | 7.0188  | 0.0194          | 22.3362 |
| 0.0083        | 1.2637 | 1600  | 6.1604  | 0.0183          | 20.2225 |
| 0.0066        | 1.5794 | 2000  | 5.9469  | 0.0176          | 19.4205 |
| 0.0065        | 1.8952 | 2400  | 5.8609  | 0.0174          | 19.0958 |
| 0.0161        | 2.1084 | 2800  | 5.8786  | 0.0167          | 18.8094 |
| 0.0157        | 2.4096 | 3200  | 5.6719  | 0.0162          | 18.4526 |
| 0.0157        | 2.7107 | 3600  | 5.6150  | 0.0160          | 18.3772 |
| 0.0063        | 3.1595 | 4000  | 5.4820  | 0.0160          | 18.0877 |
| 0.0052        | 3.4752 | 4400  | 5.4747  | 0.0161          | 18.2023 |
| 0.0049        | 3.7910 | 4800  | 5.5285  | 0.0161          | 17.9922 |
| 0.0154        | 3.9155 | 5200  | 5.5457  | 0.0159          | 18.1641 |
| 0.0142        | 4.2168 | 5600  | 5.4871  | 0.0158          | 17.9721 |
| 0.0143        | 4.5180 | 6000  | 5.5382  | 0.0157          | 18.0495 |
| 0.0155        | 4.8191 | 6400  | 5.4620  | 0.0156          | 17.9460 |
| 0.005         | 5.3710 | 6800  | 5.4875  | 0.0157          | 17.7691 |
| 0.0052        | 5.6868 | 7200  | 5.4416  | 0.0157          | 17.8646 |
| 0.0085        | 4.8653 | 7600  | 5.5002  | 0.0157          | 17.8817 |
| 0.0096        | 5.1216 | 8000  | 5.5124  | 0.0156          | 17.8264 |
| 0.0094        | 5.3776 | 8400  | 5.6387  | 0.0155          | 17.7500 |
| 0.0093        | 5.6336 | 8800  | 5.4429  | 0.0154          | 17.6736 |
| 0.01          | 5.8896 | 9200  | 5.3128  | 0.0153          | 17.2856 |
| 0.0091        | 6.1453 | 9600  | 5.2836  | 0.0153          | 17.2424 |
| 0.0088        | 6.4019 | 10000 | 0.0153  | 17.2434         | 5.2826  |
| 0.008         | 6.6579 | 10400 | 0.0153  | 17.1288         | 5.2957  |
| 0.007         | 6.9139 | 10800 | 0.0153  | 17.1680         | 5.2889  |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0