Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`cardiffnlp/twitter-xlm-roberta-base`](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) 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

@@ -4,6 +4,24 @@ datasets:
 metrics:
 - f1
 - accuracy
+pipeline_tag: text-classification
+widget:
+- text: Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@}
+    via {@bluenoterecords@} link below {{URL}}
+  example_title: topic_classification 1
+- text: Yes, including Medicare and social security saving👍
+  example_title: sentiment 1
+- text: All two of them taste like ass.
+  example_title: offensive 1
+- text: If you wanna look like a badass, have drama on social media
+  example_title: irony 1
+- text: Whoever just unfollowed me you a bitch
+  example_title: hate 1
+- text: I love swimming for the same reason I love meditating...the feeling of weightlessness.
+  example_title: emotion 1
+- text: Beautiful sunset last night from the pontoon @TupperLakeNY
+  example_title: emoji 1
+base_model: cardiffnlp/twitter-xlm-roberta-base
 model-index:
 - name: cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual
   results:
@@ -13,33 +31,17 @@ model-index:
     dataset:
       name: cardiffnlp/tweet_sentiment_multilingual
       type: all
-      split: test 
+      split: test
     metrics:
-    - name: Micro F1 (cardiffnlp/tweet_sentiment_multilingual/all)
-      type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
+    - type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
       value: 0.6931034482758621
-    - name: Macro F1 (cardiffnlp/tweet_sentiment_multilingual/all)
-      type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
+      name: Micro F1 (cardiffnlp/tweet_sentiment_multilingual/all)
+    - type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
       value: 0.692628774202147
-    - name: Accuracy (cardiffnlp/tweet_sentiment_multilingual/all)
-      type: accuracy_cardiffnlp/tweet_sentiment_multilingual/all
+      name: Macro F1 (cardiffnlp/tweet_sentiment_multilingual/all)
+    - type: accuracy_cardiffnlp/tweet_sentiment_multilingual/all
       value: 0.6931034482758621
-pipeline_tag: text-classification
-widget:
-- text: Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below {{URL}}
-  example_title: "topic_classification 1" 
-- text: Yes, including Medicare and social security saving👍
-  example_title: "sentiment 1" 
-- text: All two of them taste like ass.
-  example_title: "offensive 1" 
-- text: If you wanna look like a badass, have drama on social media
-  example_title: "irony 1" 
-- text: Whoever just unfollowed me you a bitch
-  example_title: "hate 1" 
-- text: I love swimming for the same reason I love meditating...the feeling of weightlessness.
-  example_title: "emotion 1" 
-- text: Beautiful sunset last night from the pontoon @TupperLakeNY
-  example_title: "emoji 1" 
+      name: Accuracy (cardiffnlp/tweet_sentiment_multilingual/all)
 ---
 # cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual