---
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 - full
  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: 121.00549461448435
---

<!-- 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 - full

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: 0.0375
- Wer: 121.0055

## 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: 4
- eval_batch_size: 4
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer      |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1349        | 0.2   | 1000  | 0.1227          | 256.8256 |
| 0.1098        | 0.4   | 2000  | 0.0918          | 438.2193 |
| 0.1071        | 0.6   | 3000  | 0.0839          | 286.1663 |
| 0.0837        | 0.8   | 4000  | 0.0737          | 295.5091 |
| 0.0672        | 1.0   | 5000  | 0.0611          | 293.6147 |
| 0.03          | 1.2   | 6000  | 0.0559          | 204.9680 |
| 0.0104        | 1.4   | 7000  | 0.0485          | 189.5761 |
| 0.0245        | 1.6   | 8000  | 0.0456          | 141.0698 |
| 0.0446        | 1.8   | 9000  | 0.0398          | 134.5774 |
| 0.0231        | 2.0   | 10000 | 0.0375          | 121.0055 |


### Framework versions

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