---
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
datasets:
  - arbml/mgb2
metrics:
  - wer
model-index:
  - name: Whisper Small ar - Mohammad AlMarzouq
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: ar
          split: test
          args: ar
        metrics:
          - name: Wer
            type: wer
            value: 43.14
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: ar_eg
          split: test
          args: ar
        metrics:
          - name: Wer
            type: wer
            value: 16.69
---

<!-- 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. -->

# openai/whisper-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9750
- Wer: 21.3693

## 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: 64
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3559        | 0.1   | 1000  | 0.9147          | 29.3252 |
| 0.3154        | 0.2   | 2000  | 1.1353          | 26.5718 |
| 0.359         | 0.3   | 3000  | 0.9208          | 25.3987 |
| 0.273         | 0.4   | 4000  | 0.9591          | 24.3877 |
| 0.2326        | 0.5   | 5000  | 0.9207          | 21.9052 |
| 0.2992        | 1.04  | 6000  | 0.9445          | 22.4556 |
| 0.2265        | 1.14  | 7000  | 0.9660          | 21.2230 |
| 0.2059        | 1.24  | 8000  | 0.9785          | 20.9551 |
| 0.2239        | 1.34  | 9000  | 0.9637          | 21.6300 |
| 0.2163        | 1.44  | 10000 | 0.9750          | 21.3693 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2