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---
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
should probably proofread and complete it, then remove this comment. -->
# 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 |