---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- MightyStudent/Egyptian-ASR-MGB-3
metrics:
- wer
model-index:
- name: 'Egyptian Whisper Small '
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Egyptian-ASR-MGB-3
      type: MightyStudent/Egyptian-ASR-MGB-3
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 46.28931679572398
---

<!-- 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. -->

# Egyptian Whisper Small 

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Egyptian-ASR-MGB-3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9939
- Wer: 46.2893

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.4615        | 6.8966  | 100  | 0.6496          | 48.0162 |
| 0.072         | 13.7931 | 200  | 0.7459          | 46.3990 |
| 0.0122        | 20.6897 | 300  | 0.8380          | 45.6863 |
| 0.0054        | 27.5862 | 400  | 0.8981          | 45.0764 |
| 0.0033        | 34.4828 | 500  | 0.9322          | 45.2820 |
| 0.0025        | 41.3793 | 600  | 0.9555          | 45.4670 |
| 0.002         | 48.2759 | 700  | 0.9724          | 46.1454 |
| 0.0017        | 55.1724 | 800  | 0.9843          | 45.9467 |
| 0.0016        | 62.0690 | 900  | 0.9916          | 46.0769 |
| 0.0015        | 68.9655 | 1000 | 0.9939          | 46.2893 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1