---
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
- whisper-event
metrics:
- wer
model-index:
- name: openai/whisper-medium
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0 kab
      type: mozilla-foundation/common_voice_17_0
      args: 'config: ml, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 16.15101446793939
language:
- kab
datasets:
- mozilla-foundation/common_voice_17_0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# openai/whisper-base

This is an automatic speech recognition model that also does punctuation and casing. This model is for research only, **we do not recommend using this model on production environments**.

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_17_0 kab dataset.
It achieves the following results on the evaluation set:
- Loss: 
- Wer: 

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters


### Framework versions

- Transformers 4.25.1
- Pytorch 1.10.0+cu102
- Datasets 2.8.0
- Tokenizers 0.13.2