Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`LeBenchmark/wav2vec2-FR-7K-large`](https://huggingface.co/LeBenchmark/wav2vec2-FR-7K-large) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.

How did we find this information? We performed a regular expression match on your `README.md` file to determine the connection.

**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.

For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien). Your input is invaluable to us!

README.md

@@ -1,8 +1,7 @@
 ---
-license: apache-2.0
 language: fr
+license: apache-2.0
 library_name: transformers
-thumbnail: null
 tags:
 - automatic-speech-recognition
 - hf-asr-leaderboard
@@ -17,93 +16,94 @@ datasets:
 - gigant/african_accented_french
 metrics:
 - wer
+base_model: LeBenchmark/wav2vec2-FR-7K-large
 model-index:
 - name: Fine-tuned wav2vec2-FR-7K-large model for ASR in French
   results:
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: Common Voice 11.0
       type: mozilla-foundation/common_voice_11_0
       args: fr
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 11.44
-    - name: Test WER (+LM)
-      type: wer
+      name: Test WER
+    - type: wer
       value: 9.66
+      name: Test WER (+LM)
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: Multilingual LibriSpeech (MLS)
       type: facebook/multilingual_librispeech
       args: french
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 5.93
-    - name: Test WER (+LM)
-      type: wer
+      name: Test WER
+    - type: wer
       value: 5.13
+      name: Test WER (+LM)
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: VoxPopuli
       type: facebook/voxpopuli
       args: fr
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 9.33
-    - name: Test WER (+LM)
-      type: wer
+      name: Test WER
+    - type: wer
       value: 8.51
+      name: Test WER (+LM)
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: African Accented French
       type: gigant/african_accented_french
       args: fr
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 16.22
-    - name: Test WER (+LM)
-      type: wer
+      name: Test WER
+    - type: wer
       value: 15.39
+      name: Test WER (+LM)
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: Robust Speech Event - Dev Data
       type: speech-recognition-community-v2/dev_data
       args: fr
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 16.56
-    - name: Test WER (+LM)
-      type: wer
+      name: Test WER
+    - type: wer
       value: 12.96
+      name: Test WER (+LM)
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: Fleurs
       type: google/fleurs
       args: fr_fr
     metrics:
-    - name: Test WER
-      type: wer
-      value: 10.10
-    - name: Test WER (+LM)
-      type: wer
+    - type: wer
+      value: 10.1
+      name: Test WER
+    - type: wer
       value: 8.84
+      name: Test WER (+LM)
 ---
 
 # Fine-tuned wav2vec2-FR-7K-large model for ASR in French