---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small AR - Mohammed Bakheet
  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: test
      args: ar
    metrics:
    - name: Wer
      type: wer
      value: 20.773418434390837
---

<!-- 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 - Mohammed Bakheet

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: 0.3144
- Wer: 20.7734

## 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: 5e-07
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.5507        | 0.2079 | 500   | 0.3695          | 29.2247 |
| 0.2802        | 0.4158 | 1000  | 0.3148          | 26.7299 |
| 0.2408        | 0.6236 | 1500  | 0.2970          | 24.2538 |
| 0.2208        | 0.8315 | 2000  | 0.2728          | 23.3020 |
| 0.1811        | 1.0394 | 2500  | 0.2665          | 22.3935 |
| 0.1096        | 1.2473 | 3000  | 0.2641          | 21.8998 |
| 0.1068        | 1.4552 | 3500  | 0.2568          | 21.6125 |
| 0.1042        | 1.6630 | 4000  | 0.2516          | 21.0512 |
| 0.1001        | 1.8709 | 4500  | 0.2472          | 20.4092 |
| 0.0827        | 2.0788 | 5000  | 0.2469          | 20.3848 |
| 0.0672        | 2.2869 | 5500  | 0.2665          | 21.1357 |
| 0.0673        | 2.4948 | 6000  | 0.2674          | 21.5093 |
| 0.0681        | 2.7026 | 6500  | 0.2635          | 20.6101 |
| 0.0661        | 2.9105 | 7000  | 0.2602          | 20.5069 |
| 0.0494        | 3.1184 | 7500  | 0.2708          | 20.5444 |
| 0.0352        | 3.3263 | 8000  | 0.2688          | 20.5181 |
| 0.0338        | 3.5341 | 8500  | 0.2717          | 20.2515 |
| 0.0318        | 3.7420 | 9000  | 0.2723          | 20.2403 |
| 0.0309        | 3.9499 | 9500  | 0.2711          | 20.1727 |
| 0.022         | 4.1578 | 10000 | 0.2758          | 20.1577 |
| 0.0229        | 8.7351 | 10500 | 0.2930          | 21.1019 |
| 0.0217        | 9.1508 | 11000 | 0.3086          | 20.9874 |
| 0.0168        | 9.5666 | 11500 | 0.3026          | 20.7847 |
| 0.0162        | 9.9823 | 12000 | 0.3144          | 20.7734 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3