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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: 0.1077
- Wer: 0.2309
## 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: 8
- total_train_batch_size: 64
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 3.3412 | 1.0 | 157 | 0.1041 | 0.2149 |
| 3.0121 | 2.0 | 314 | 0.1054 | 0.2123 |
| 2.6811 | 3.0 | 471 | 0.1033 | 0.2079 |
| 2.2468 | 4.0 | 628 | 0.1062 | 0.2163 |
| 2.1438 | 5.0 | 785 | 0.1029 | 0.2168 |
| 1.8098 | 6.0 | 942 | 0.1035 | 0.2131 |
| 1.7488 | 7.0 | 1099 | 0.1023 | 0.2190 |
| 1.52 | 8.0 | 1256 | 0.1020 | 0.2116 |
| 1.431 | 9.0 | 1413 | 0.1013 | 0.2112 |
| 1.3151 | 10.0 | 1570 | 0.1005 | 0.2168 |
| 1.2219 | 11.0 | 1727 | 0.1011 | 0.2107 |
| 1.1879 | 12.0 | 1884 | 0.1003 | 0.2097 |
| 1.1158 | 13.0 | 2041 | 0.1007 | 0.2098 |
| 1.0995 | 14.0 | 2198 | 0.0998 | 0.2095 |
| 1.0596 | 14.9088 | 2340 | 0.1001 | 0.2107 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
|