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---
language:
- fr
license: apache-2.0
tags:
- whisper
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_15_0
- BrunoHays/multilingual-tedx-fr
- PolyAI/minds14
- facebook/multilingual_librispeech
- facebook/voxpopuli
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper tiny French
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset1:
name: mozilla-foundation/common_voice_15_0 fr
type: mozilla-foundation/common_voice_15_0
config: fr
split: test
args: fr
metrics:
- name: Wer
type: wer
value: 40.0
dataset2:
name: facebook/multilingual_librispeech fr
type: facebook/multilingual_librispeech
config: fr
split: test
args: fr
wer : 26.1
dataset3:
name: facebook/voxpopuli fr
type: facebook/voxpopuli
config: fr
split: test
args: fr
wer : 29.4
dataset4:
name: google/fleurs fr
type: google/fleurs
config: fr
split: test
args: fr
wer : 33.7
---
<!-- 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 tiny fr - JaepaX
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fr datasets.
## WER Result
It achieves the following results on the evaluation sets
- Mulit-Libri : "26.1",
- common : "40.0"
- voxpopuli : "29.4"
- fleurs : "33.7" |