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---
language:
- is
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
datasets:
- language-and-voice-lab/samromur_asr
- language-and-voice-lab/althingi_asr
- language-and-voice-lab/malromur_asr
- language-and-voice-lab/samromur_children
- language-and-voice-lab/raddromur_asr
metrics:
- wer
pinned: false
model-index:
- name: Whisper medium is
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: samromur
type: language-and-voice-lab/samromur_asr
config: samromur_asr
split: test
metrics:
- type: wer
value: 10.08%
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: is_is
split: test
metrics:
- type: wer
value: 13.94
name: WER
---
# openai/whisper-medium
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the samromur, malromur, raddromur and althingi datasets.
It achieves the following results on the evaluation set, the output is lowercased and punctuation is removed:
- Google Fleurs 13.94% WER
- Samrómur 10.08% WER
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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