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---
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: 0.0853
- Wer: 0.1969
## 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 2.0599 | 0.5858 | 1000 | 0.0910 | 0.2075 |
| 1.6156 | 1.1716 | 2000 | 0.0921 | 0.1917 |
| 1.5706 | 1.7575 | 3000 | 0.0891 | 0.1953 |
| 1.3401 | 2.3433 | 4000 | 0.0880 | 0.1882 |
| 1.2238 | 2.9291 | 5000 | 0.0865 | 0.1886 |
| 1.0654 | 3.5149 | 6000 | 0.0860 | 0.1922 |
| 1.0904 | 4.1008 | 7000 | 0.0859 | 0.2000 |
| 1.2607 | 4.6866 | 8000 | 0.0872 | 0.1882 |
| 1.147 | 5.2724 | 9000 | 0.0870 | 0.1944 |
| 1.1237 | 5.8582 | 10000 | 0.0856 | 0.1905 |
| 1.0093 | 6.4441 | 11000 | 0.0849 | 0.2001 |
| 0.9993 | 7.0299 | 12000 | 0.0839 | 0.1888 |
| 0.8718 | 7.6157 | 13000 | 0.0844 | 0.1894 |
| 0.8877 | 8.2015 | 14000 | 0.0838 | 0.1908 |
| 0.8187 | 8.7873 | 15000 | 0.0843 | 0.1957 |
| 0.8235 | 9.3732 | 16000 | 0.0838 | 0.1975 |
| 0.7972 | 9.9590 | 17000 | 0.0835 | 0.1911 |
| 0.8203 | 10.5448 | 18000 | 0.0844 | 0.1866 |
| 0.8593 | 11.1306 | 19000 | 0.0843 | 0.1916 |
| 0.8279 | 11.7165 | 20000 | 0.0840 | 0.1905 |
| 0.806 | 12.3023 | 21000 | 0.0827 | 0.1897 |
| 0.8343 | 12.8881 | 22000 | 0.0832 | 0.1891 |
| 0.7252 | 13.4739 | 23000 | 0.0830 | 0.1845 |
| 0.7685 | 14.0598 | 24000 | 0.0830 | 0.1919 |
| 0.7085 | 14.6456 | 25000 | 0.0829 | 0.1975 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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