---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- automatic-speech-recognition
- whisper
- arabic
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-ar-resturant-6
  results: []
---

<!-- 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. -->

# whisper-large-v3-ar-resturant-6

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the heikal/arabic_call_splitted_6and7 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6293
- Wer: 64.3505

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0004        | 111.1111 | 1000 | 1.6293          | 64.3505 |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1