---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- DrAliGomaa/ar-eg-dataset
metrics:
- wer
model-index:
- name: whisper-small-ar-test-draligomaa-dataset
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: draligomaa-dataset
      type: DrAliGomaa/ar-eg-dataset
      config: default
      split: train[500:]
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 32.35294117647059
---

<!-- 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-small-ar-test-draligomaa-dataset

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the draligomaa-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5144
- Wer Ortho: 32.3529
- Wer: 32.3529

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 20
- training_steps: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.0476        | 6.25  | 100  | 0.4496          | 32.1429   | 32.1429 |
| 0.0051        | 12.5  | 200  | 0.5144          | 32.3529   | 32.3529 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1