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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 - YA
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 - YA
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: 0.0033
- Wer: 0.0497
- Cer: 0.0200
## 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: 2
- total_train_batch_size: 16
- optimizer: Use 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: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0024 | 1.0 | 320 | 0.0034 | 0.0440 | 0.0180 |
| 0.0014 | 2.0 | 640 | 0.0049 | 0.0653 | 0.0257 |
| 0.0013 | 3.0 | 960 | 0.0057 | 0.0766 | 0.0283 |
| 0.0007 | 4.0 | 1280 | 0.0057 | 0.0681 | 0.0290 |
| 0.0004 | 5.0 | 1600 | 0.0057 | 0.0617 | 0.0253 |
| 0.0002 | 6.0 | 1920 | 0.0060 | 0.0662 | 0.0244 |
| 0.0002 | 7.0 | 2240 | 0.0068 | 0.0624 | 0.0237 |
| 0.0003 | 8.0 | 2560 | 0.0061 | 0.0652 | 0.0259 |
| 0.0003 | 9.0 | 2880 | 0.0067 | 0.0648 | 0.0252 |
| 0.0004 | 10.0 | 3200 | 0.0062 | 0.0670 | 0.0259 |
| 0.0002 | 11.0 | 3520 | 0.0061 | 0.0610 | 0.0230 |
| 0.0001 | 12.0 | 3840 | 0.0064 | 0.0581 | 0.0217 |
| 0.0001 | 13.0 | 4160 | 0.0061 | 0.0576 | 0.0217 |
| 0.0 | 14.0 | 4480 | 0.0062 | 0.0594 | 0.0235 |
| 0.0 | 15.0 | 4800 | 0.0066 | 0.0630 | 0.0251 |
| 0.0 | 16.0 | 5120 | 0.0069 | 0.0581 | 0.0240 |
| 0.0 | 17.0 | 5440 | 0.0070 | 0.0579 | 0.0228 |
| 0.0 | 18.0 | 5760 | 0.0071 | 0.0586 | 0.0232 |
| 0.0 | 19.0 | 6080 | 0.0072 | 0.0590 | 0.0239 |
| 0.0 | 20.0 | 6400 | 0.0072 | 0.0576 | 0.0234 |
| 0.0 | 21.0 | 6720 | 0.0073 | 0.0574 | 0.0239 |
| 0.0 | 22.0 | 7040 | 0.0073 | 0.0577 | 0.0240 |
| 0.0 | 23.0 | 7360 | 0.0074 | 0.0577 | 0.0240 |
| 0.0 | 24.0 | 7680 | 0.0076 | 0.0613 | 0.0246 |
| 0.0 | 25.0 | 8000 | 0.0074 | 0.0581 | 0.0244 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3
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