---
language:
- ar
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- arab
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small ar - Atishay Sharma
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: arabic
      type: arab
      config: default
      split: train
      args: 'config: ar, split: test'
    metrics:
    - type: wer
      value: 4.545454545454546
      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. -->

# Whisper Small ar - Atishay Sharma

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the arabic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0922
- Wer: 4.5455

## 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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0           | 500.0 | 500  | 0.0922          | 4.5455 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2