---
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
metrics:
- wer
model-index:
- name: whisper-medium-arabic-suite-II
  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: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 15.6083
datasets:
- mozilla-foundation/common_voice_11_0
---

<!-- 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-medium-arabic-suite-II

This model is a fine-tuned version of [Seyfelislem/whisper-medium-arabic-suite](https://huggingface.co/Seyfelislem/whisper-medium-arabic-suite) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1897
- Wer: 15.6083

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.088         | 0.67  | 800  | 0.1897          | 15.6083 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.0
- Datasets 2.10.2.dev0
- Tokenizers 0.13.2