---
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ahishamm/QURANICWhisperDataset
metrics:
- wer
model-index:
- name: QURANIC Whisper Large V3 - 2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: QURANICWhisperDataset
      type: ahishamm/QURANICWhisperDataset
      args: 'config: ar, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 112.02681655041647
---

<!-- 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. -->

# QURANIC Whisper Large V3 - 2

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the QURANICWhisperDataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1663
- Wer: 112.0268

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0862        | 2.0   | 1000 | 0.1308          | 162.4365 |
| 0.0489        | 4.0   | 2000 | 0.1305          | 168.4432 |
| 0.0111        | 6.0   | 3000 | 0.1499          | 193.2011 |
| 0.0013        | 8.0   | 4000 | 0.1663          | 112.0268 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.1