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

@@ -11,76 +11,61 @@ tags:
 - zh-HK
 datasets:
 - mozilla-foundation/common_voice_8_0
+base_model: facebook/wav2vec2-xls-r-300m
 model-index:
 - name: XLS-R-300M - Chinese_HongKong (Cantonese)
   results:
   - task:
-      name: Automatic Speech Recognition
       type: automatic-speech-recognition
+      name: Automatic Speech Recognition
     dataset:
       name: Common Voice 8
       type: mozilla-foundation/common_voice_8_0
       args: zh-hk
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 0.8111349803079126
-    - name: Test CER
-      type: cer
+      name: Test WER
+    - type: cer
       value: 0.21962250882996914
+      name: Test CER
+    - type: wer
+      value: 0.8055853920515574
+      name: Test WER with LM
+    - type: cer
+      value: 0.21578686612008757
+      name: Test CER with 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: zh-hk
     metrics:
-    - name: Test WER
-      type: wer
+    - type: wer
       value: 1.0
-    - name: Test CER
-      type: cer
+      name: Test WER
+    - type: cer
       value: 0.6160564326503191
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 8
-      type: mozilla-foundation/common_voice_8_0
-      args: zh-HK
-    metrics:
-    - name: Test WER with LM
-      type: wer
-      value: 0.8055853920515574
-    - name: Test CER with LM
-      type: cer
-      value: 0.21578686612008757
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Robust Speech Event - Dev Data
-      type: speech-recognition-community-v2/dev_data
-      args: zh-HK
-    metrics:
-    - name: Test WER with LM
-      type: wer
+      name: Test CER
+    - type: wer
       value: 1.0012453300124533
-    - name: Test CER with LM
-      type: cer
+      name: Test WER with LM
+    - type: cer
       value: 0.6153006382264025
+      name: Test CER with LM
   - 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: zh-HK
     metrics:
-    - name: Test CER
-      type: cer
+    - type: cer
       value: 61.55
+      name: Test CER
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You