Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`facebook/wav2vec2-xls-r-300m`](https://huggingface.co/facebook/wav2vec2-xls-r-300m) 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

@@ -14,76 +14,77 @@ datasets:
 - mozilla-foundation/common_voice_8_0
 - collectivat/tv3_parla
 - projecte-aina/parlament_parla
+base_model: facebook/wav2vec2-xls-r-300m
 model-index:
 - name: wav2vec2-xls-r-1b-ca-lm
   results:
   - task:
-      name: Speech Recognition
       type: automatic-speech-recognition
+      name: Speech Recognition
     dataset:
       name: mozilla-foundation/common_voice_8_0 ca
       type: mozilla-foundation/common_voice_8_0
       args: ca
     metrics:
-    - name: Test WER
-      type: wer
-      value: 6.0722669958130644
-    - name: Test CER
-      type: cer
-      value: 1.9180697705166526
+    - type: wer
+      value: 6.072266995813065
+      name: Test WER
+    - type: cer
+      value: 1.9180697705166525
+      name: Test CER
   - task:
-      name: Speech Recognition
       type: automatic-speech-recognition
+      name: Speech Recognition
     dataset:
       name: projecte-aina/parlament_parla ca
       type: projecte-aina/parlament_parla
       args: clean
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 5.139820371024042
-    - name: Test CER
-      type: cer
-      value: 2.0163620128164722
+      name: Test WER
+    - type: cer
+      value: 2.0163620128164723
+      name: Test CER
   - task:
-      name: Speech Recognition
       type: automatic-speech-recognition
+      name: Speech Recognition
     dataset:
       name: collectivat/tv3_parla ca
       type: collectivat/tv3_parla
       args: ca
     metrics:
-    - name: Test WER
-      type: wer
-      value: 11.207991684952073
-    - name: Test CER
-      type: cer
+    - type: wer
+      value: 11.207991684952074
+      name: Test WER
+    - type: cer
       value: 7.32119307305963
+      name: Test CER
   - task:
-      name: Speech Recognition
       type: automatic-speech-recognition
+      name: Speech Recognition
     dataset:
       name: Robust Speech Event - Catalan Dev Data
       type: speech-recognition-community-v2/dev_data
       args: ca
     metrics:
-    - name: Test WER
-      type: wer
-      value: 22.870153690468661
-    - name: Test CER
-      type: cer
+    - type: wer
+      value: 22.870153690468662
+      name: Test WER
+    - type: cer
       value: 13.59039190897598
+      name: Test CER
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: Robust Speech Event - Test Data
       type: speech-recognition-community-v2/eval_data
       args: ca
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 15.41
+      name: Test WER
 ---
 
 # wav2vec2-xls-r-1b-ca-lm