---
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ahishamm/whisperQURANIC
metrics:
- wer
model-index:
- name: QURANIC Whisper Large V3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: whisperQURANIC
      type: ahishamm/whisperQURANIC
      args: 'config: ar, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 268.8141178069162
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the whisperQURANIC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0238
- Wer: 268.8141

## 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: 1
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1467        | 0.4   | 200  | 0.1302          | 42.9071  |
| 0.1226        | 0.8   | 400  | 0.0958          | 156.6683 |
| 0.0746        | 1.2   | 600  | 0.0772          | 494.4510 |
| 0.0868        | 1.6   | 800  | 0.0678          | 252.8552 |
| 0.0801        | 2.0   | 1000 | 0.0560          | 361.0673 |
| 0.0552        | 2.4   | 1200 | 0.0473          | 153.8658 |
| 0.053         | 2.8   | 1400 | 0.0399          | 310.5204 |
| 0.0421        | 3.2   | 1600 | 0.0308          | 305.3961 |
| 0.0291        | 3.6   | 1800 | 0.0266          | 242.5182 |
| 0.0303        | 4.0   | 2000 | 0.0238          | 268.8141 |


### Framework versions

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