---
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: 0.0847
- Wer: 0.1936

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 2.1291        | 0.5858  | 1000  | 0.0912          | 0.1978 |
| 1.7057        | 1.1716  | 2000  | 0.0912          | 0.2003 |
| 1.7162        | 1.7575  | 3000  | 0.0912          | 0.2060 |
| 1.4996        | 2.3433  | 4000  | 0.0901          | 0.2047 |
| 1.3942        | 2.9291  | 5000  | 0.0883          | 0.1951 |
| 1.2285        | 3.5149  | 6000  | 0.0876          | 0.1957 |
| 1.0637        | 4.1008  | 7000  | 0.0873          | 0.1920 |
| 1.1144        | 4.6866  | 8000  | 0.0865          | 0.1927 |
| 1.0164        | 5.2724  | 9000  | 0.0858          | 0.1923 |
| 0.9812        | 5.8582  | 10000 | 0.0856          | 0.1941 |
| 0.8927        | 6.4441  | 11000 | 0.0849          | 0.2017 |
| 0.8936        | 7.0299  | 12000 | 0.0844          | 0.1961 |
| 0.8718        | 7.6157  | 13000 | 0.0854          | 0.1979 |
| 0.9019        | 8.2015  | 14000 | 0.0847          | 0.1854 |
| 0.8293        | 8.7873  | 15000 | 0.0847          | 0.1983 |
| 0.8363        | 9.3732  | 16000 | 0.0842          | 0.1982 |
| 0.8034        | 9.9590  | 17000 | 0.0840          | 0.1975 |
| 0.8462        | 10.5448 | 18000 | 0.0855          | 0.1953 |
| 0.8824        | 11.1306 | 19000 | 0.0848          | 0.1930 |
| 0.8591        | 11.7165 | 20000 | 0.0849          | 0.1838 |
| 0.8339        | 12.3023 | 21000 | 0.0842          | 0.1863 |
| 0.8573        | 12.8881 | 22000 | 0.0836          | 0.1926 |
| 0.7445        | 13.4739 | 23000 | 0.0839          | 0.1842 |
| 0.783         | 14.0598 | 24000 | 0.0836          | 0.1842 |
| 0.7263        | 14.6456 | 25000 | 0.0839          | 0.1824 |
| 0.7634        | 15.2314 | 26000 | 0.0835          | 0.1826 |
| 0.7379        | 15.8172 | 27000 | 0.0834          | 0.1829 |
| 0.7902        | 16.4030 | 28000 | 0.0842          | 0.1811 |
| 0.8261        | 16.9889 | 29000 | 0.0841          | 0.1849 |
| 0.7531        | 17.5747 | 30000 | 0.0840          | 0.1867 |
| 0.7166        | 18.1605 | 31000 | 0.0839          | 0.1905 |
| 0.7976        | 18.7463 | 32000 | 0.0841          | 0.1838 |
| 0.7008        | 19.3322 | 33000 | 0.0835          | 0.1864 |
| 0.707         | 19.9180 | 34000 | 0.0833          | 0.1872 |
| 0.6865        | 20.5038 | 35000 | 0.0835          | 0.1844 |
| 0.6927        | 21.0896 | 36000 | 0.0834          | 0.1882 |
| 0.7014        | 21.6755 | 37000 | 0.0835          | 0.1861 |
| 0.6951        | 22.2613 | 38000 | 0.0833          | 0.1874 |
| 0.6848        | 22.8471 | 39000 | 0.0834          | 0.1927 |
| 0.7096        | 23.4329 | 40000 | 0.0834          | 0.1936 |
| 0.6952        | 24.0187 | 41000 | 0.0835          | 0.1933 |
| 0.692         | 24.6046 | 42000 | 0.0833          | 0.1930 |
| 0.6552        | 25.1904 | 43000 | 0.0831          | 0.1867 |
| 0.6641        | 25.7762 | 44000 | 0.0832          | 0.1874 |
| 0.6921        | 26.3620 | 45000 | 0.0833          | 0.1880 |
| 0.6894        | 26.9479 | 46000 | 0.0832          | 0.1855 |
| 0.7041        | 27.5337 | 47000 | 0.0827          | 0.1855 |
| 0.6452        | 28.1195 | 48000 | 0.0830          | 0.1882 |
| 0.6682        | 28.7053 | 49000 | 0.0828          | 0.1863 |
| 0.6357        | 29.2912 | 50000 | 0.0829          | 0.1877 |
| 0.6645        | 29.8770 | 51000 | 0.0831          | 0.1898 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1