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---
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