Upload README.md

README.md

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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"