---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- sermonar
metrics:
- wer
model-index:
- name: whisper small ar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: sermonarr
      type: sermonar
      config: ar
      split: test[:2%]
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 150.6172839506173
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the sermonarr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5258
- Wer: 150.6173

## 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: 16
- 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: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8749        | 0.32  | 1000 | 0.5855          | 150.4274 |
| 0.6537        | 0.65  | 2000 | 0.5461          | 130.5793 |
| 0.7103        | 0.97  | 3000 | 0.5241          | 278.2526 |
| 0.6544        | 1.29  | 4000 | 0.5258          | 150.6173 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3