---
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: QURANIC Whisper Large V3 - revised
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common_voice_16_1
      type: mozilla-foundation/common_voice_16_1
      config: ar
      split: None
      args: 'config: ar, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 163.38589913248052
---

<!-- 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 - revised

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2252
- Wer: 163.3859

## 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: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer      |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3095        | 0.21  | 2000  | 0.3293          | 155.0801 |
| 0.2412        | 0.41  | 4000  | 0.3059          | 287.9687 |
| 0.1762        | 0.62  | 6000  | 0.2843          | 152.7845 |
| 0.1906        | 0.82  | 8000  | 0.2645          | 124.8897 |
| 0.0952        | 1.03  | 10000 | 0.2535          | 129.0233 |
| 0.0955        | 1.24  | 12000 | 0.2567          | 141.4259 |
| 0.0865        | 1.44  | 14000 | 0.2360          | 205.5690 |
| 0.1363        | 1.65  | 16000 | 0.2288          | 187.0938 |
| 0.1038        | 1.86  | 18000 | 0.2197          | 178.2311 |
| 0.062         | 2.06  | 20000 | 0.2252          | 163.3859 |


### Framework versions

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