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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: 0.0867
- Wer: 0.1925
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.7381 | 1.0 | 469 | 0.0864 | 0.1945 |
| 1.6182 | 2.0 | 938 | 0.0902 | 0.2013 |
| 1.2194 | 3.0 | 1407 | 0.0893 | 0.1911 |
| 1.0951 | 4.0 | 1876 | 0.0881 | 0.2001 |
| 1.0233 | 5.0 | 2345 | 0.0867 | 0.1979 |
| 0.9062 | 6.0 | 2814 | 0.0864 | 0.1995 |
| 0.8866 | 7.0 | 3283 | 0.0852 | 0.1992 |
| 0.8074 | 8.0 | 3752 | 0.0858 | 0.1922 |
| 0.7585 | 9.0 | 4221 | 0.0853 | 0.1882 |
| 0.6978 | 10.0 | 4690 | 0.0849 | 0.1911 |
| 0.6625 | 11.0 | 5159 | 0.0845 | 0.1901 |
| 0.6375 | 12.0 | 5628 | 0.0839 | 0.1861 |
| 0.6057 | 13.0 | 6097 | 0.0838 | 0.1883 |
| 0.5872 | 14.0 | 6566 | 0.0839 | 0.1895 |
| 0.5605 | 14.9685 | 7020 | 0.0838 | 0.1891 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
|