---
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