---
language:
- ar
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- zolfa
metrics:
- wer
model-index:
- name: Zolfa-raghadomar
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Zolfa Dataset
      type: zolfa
      args: 'config: ar, split: test'
    metrics:
    - type: wer
      value: 8.571428571428571
      name: Wer
---

<!-- 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. -->

# Zolfa-raghadomar

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Zolfa Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2371
- Wer: 8.5714

## 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: 4
- 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: 5
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0671        | 0.6993 | 100  | 0.2041          | 12.8571 |
| 0.0247        | 1.3986 | 200  | 0.2290          | 10.4082 |
| 0.0071        | 2.0979 | 300  | 0.2219          | 9.7959  |
| 0.0102        | 2.7972 | 400  | 0.2215          | 26.9388 |
| 0.0046        | 3.4965 | 500  | 0.2192          | 8.5714  |
| 0.005         | 4.1958 | 600  | 0.2401          | 9.1837  |
| 0.0074        | 4.8951 | 700  | 0.2296          | 7.9592  |
| 0.0006        | 5.5944 | 800  | 0.2363          | 9.1837  |
| 0.0002        | 6.2937 | 900  | 0.2366          | 8.5714  |
| 0.0013        | 6.9930 | 1000 | 0.2371          | 8.5714  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1