---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small ar - younes matrab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ar
      split: None
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 61.65413533834586
---

<!-- 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 - younes matrab

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8027
- Wer: 61.6541

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.7188        | 0.4167 | 10   | 2.7773          | 67.1053 |
| 1.6979        | 0.8333 | 20   | 2.4033          | 66.5414 |
| 1.3932        | 1.25   | 30   | 1.9422          | 66.3534 |
| 1.0467        | 1.6667 | 40   | 1.6225          | 65.2256 |
| 0.8824        | 2.0833 | 50   | 1.3586          | 64.4737 |
| 0.5935        | 2.5    | 60   | 1.0915          | 62.4060 |
| 0.4491        | 2.9167 | 70   | 0.8986          | 63.3459 |
| 0.3438        | 3.3333 | 80   | 0.8473          | 61.6541 |
| 0.2915        | 3.75   | 90   | 0.8132          | 60.1504 |
| 0.2391        | 4.1667 | 100  | 0.8027          | 61.6541 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1