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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: 0.0847
- 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
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