---
library_name: transformers
language:
- ar
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- EMahdi/WhisperFinetune
metrics:
- wer
model-index:
- name: Whisper Large V3 Turbo Finetune Ar - EMahdi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: EMahdi/WhisperFinetune Sudanese Corpus
      type: EMahdi/WhisperFinetune
      args: 'config: sudanese_corpus, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 42.80180761781795
---

<!-- 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 Turbo Finetune Ar - EMahdi

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the EMahdi/WhisperFinetune Sudanese Corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8721
- Wer: 42.8018

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2464        | 1.0   | 89   | 0.9025          | 71.2072 |
| 0.7343        | 2.0   | 178  | 0.7835          | 55.7779 |
| 0.5441        | 3.0   | 267  | 0.7463          | 56.3105 |
| 0.4076        | 4.0   | 356  | 0.7532          | 47.5468 |
| 0.325         | 5.0   | 445  | 0.7811          | 51.4526 |
| 0.2635        | 6.0   | 534  | 0.8050          | 62.1369 |
| 0.1866        | 7.0   | 623  | 0.8226          | 45.7715 |
| 0.1171        | 8.0   | 712  | 0.8406          | 45.4810 |
| 0.0679        | 9.0   | 801  | 0.8664          | 43.5119 |
| 0.0399        | 10.0  | 890  | 0.8721          | 42.8018 |


### Framework versions

- Transformers 4.45.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3