Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`cardiffnlp/twitter-roberta-base-dec2021`](https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2021) 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).

If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!

README.md

@@ -5,76 +5,77 @@ metrics:
 - f1
 - precision
 - recall
+pipeline_tag: token-classification
+widget:
+- text: 'Get the all-analog Classic Vinyl Edition of `Takin'' Off` Album from {@herbiehancock@}
+    via {@bluenoterecords@} link below: {{URL}}'
+  example_title: NER Example 1
+base_model: cardiffnlp/twitter-roberta-base-dec2021
 model-index:
 - name: tner/twitter-roberta-base-dec2021-tweetner7-2021
   results:
   - task:
-      name: Token Classification
       type: token-classification
+      name: Token Classification
     dataset:
       name: tner/tweetner7
       type: tner/tweetner7
       args: tner/tweetner7
     metrics:
-    - name: F1 (test_2021)
-      type: f1
+    - type: f1
       value: 0.6346897022050466
-    - name: Precision (test_2021)
-      type: precision
+      name: F1 (test_2021)
+    - type: precision
       value: 0.6240500670540903
-    - name: Recall (test_2021)
-      type: recall
+      name: Precision (test_2021)
+    - type: recall
       value: 0.6456984273820536
-    - name: Macro F1 (test_2021)
-      type: f1_macro
+      name: Recall (test_2021)
+    - type: f1_macro
       value: 0.586830362928695
-    - name: Macro Precision (test_2021)
-      type: precision_macro
+      name: Macro F1 (test_2021)
+    - type: precision_macro
       value: 0.5777962671668668
-    - name: Macro Recall (test_2021)
-      type: recall_macro
+      name: Macro Precision (test_2021)
+    - type: recall_macro
       value: 0.5983908809408913
-    - name: Entity Span F1 (test_2021)
-      type: f1_entity_span
+      name: Macro Recall (test_2021)
+    - type: f1_entity_span
       value: 0.77487922705314
-    - name: Entity Span Precision (test_2020)
-      type: precision_entity_span
+      name: Entity Span F1 (test_2021)
+    - type: precision_entity_span
       value: 0.7618462226195798
-    - name: Entity Span Recall (test_2021)
-      type: recall_entity_span
+      name: Entity Span Precision (test_2020)
+    - type: recall_entity_span
       value: 0.7883659072510697
-    - name: F1 (test_2020)
-      type: f1
+      name: Entity Span Recall (test_2021)
+    - type: f1
       value: 0.6225596529284164
-    - name: Precision (test_2020)
-      type: precision
+      name: F1 (test_2020)
+    - type: precision
       value: 0.6519023282226007
-    - name: Recall (test_2020)
-      type: recall
+      name: Precision (test_2020)
+    - type: recall
       value: 0.5957446808510638
-    - name: Macro F1 (test_2020)
-      type: f1_macro
+      name: Recall (test_2020)
+    - type: f1_macro
       value: 0.578847416026638
-    - name: Macro Precision (test_2020)
-      type: precision_macro
+      name: Macro F1 (test_2020)
+    - type: precision_macro
       value: 0.6085991227224318
-    - name: Macro Recall (test_2020)
-      type: recall_macro
+      name: Macro Precision (test_2020)
+    - type: recall_macro
       value: 0.5537596756202443
-    - name: Entity Span F1 (test_2020)
-      type: f1_entity_span
+      name: Macro Recall (test_2020)
+    - type: f1_entity_span
       value: 0.7413232104121477
-    - name: Entity Span Precision (test_2020)
-      type: precision_entity_span
+      name: Entity Span F1 (test_2020)
+    - type: precision_entity_span
       value: 0.7762634866553095
-    - name: Entity Span Recall (test_2020)
-      type: recall_entity_span
+      name: Entity Span Precision (test_2020)
+    - type: recall_entity_span
       value: 0.7093928386092372
-
-pipeline_tag: token-classification
-widget:
-- text: "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}"
-  example_title: "NER Example 1"
+      name: Entity Span Recall (test_2020)
 ---
 # tner/twitter-roberta-base-dec2021-tweetner7-2021