---
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-segments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0253
- Wer: 0.1830

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0158        | 1.0   | 100  | 0.0179          | 0.2185 |
| 0.0131        | 2.0   | 200  | 0.0161          | 0.2154 |
| 0.0105        | 3.0   | 300  | 0.0148          | 0.2059 |
| 0.0066        | 4.0   | 400  | 0.0144          | 0.2011 |
| 0.0046        | 5.0   | 500  | 0.0145          | 0.2011 |
| 0.0021        | 6.0   | 600  | 0.0150          | 0.1985 |
| 0.0012        | 7.0   | 700  | 0.0154          | 0.1945 |
| 0.0004        | 8.0   | 800  | 0.0161          | 0.1890 |
| 0.0002        | 9.0   | 900  | 0.0169          | 0.1894 |
| 0.0001        | 10.0  | 1000 | 0.0177          | 0.1899 |
| 0.0           | 11.0  | 1100 | 0.0185          | 0.1842 |
| 0.0           | 12.0  | 1200 | 0.0193          | 0.1850 |
| 0.0           | 13.0  | 1300 | 0.0203          | 0.1839 |
| 0.0           | 14.0  | 1400 | 0.0214          | 0.1844 |
| 0.0           | 15.0  | 1500 | 0.0224          | 0.1804 |
| 0.0           | 16.0  | 1600 | 0.0234          | 0.1833 |
| 0.0           | 17.0  | 1700 | 0.0243          | 0.1818 |
| 0.0           | 18.0  | 1800 | 0.0253          | 0.1830 |
| 0.0           | 19.0  | 1900 | 0.0259          | 0.1854 |
| 0.0           | 20.0  | 2000 | 0.0261          | 0.1854 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3