Librarian Bot: Add base_model information to model

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

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: roberta-large
 model-index:
 - name: tner/roberta-large-tweetner7-2020-selflabel2020-all
   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: 0.6545742216194834
-    - name: Precision (test_2021)
-      type: precision
+      name: F1 (test_2021)
+    - type: precision
       value: 0.640070726047077
-    - name: Recall (test_2021)
-      type: recall
+      name: Precision (test_2021)
+    - type: recall
       value: 0.669750231267345
-    - name: Macro F1 (test_2021)
-      type: f1_macro
+      name: Recall (test_2021)
+    - type: f1_macro
       value: 0.6038933000880791
-    - name: Macro Precision (test_2021)
-      type: precision_macro
+      name: Macro F1 (test_2021)
+    - type: precision_macro
       value: 0.5872465756589016
-    - name: Macro Recall (test_2021)
-      type: recall_macro
+      name: Macro Precision (test_2021)
+    - type: recall_macro
       value: 0.6275044421067731
-    - name: Entity Span F1 (test_2021)
-      type: f1_entity_span
+      name: Macro Recall (test_2021)
+    - type: f1_entity_span
       value: 0.7917043399638336
-    - name: Entity Span Precision (test_2020)
-      type: precision_entity_span
+      name: Entity Span F1 (test_2021)
+    - type: precision_entity_span
       value: 0.7741186871477511
-    - name: Entity Span Recall (test_2021)
-      type: recall_entity_span
+      name: Entity Span Precision (test_2020)
+    - type: recall_entity_span
       value: 0.8101075517520527
-    - name: F1 (test_2020)
-      type: f1
+      name: Entity Span Recall (test_2021)
+    - type: f1
       value: 0.6623235613463626
-    - name: Precision (test_2020)
-      type: precision
+      name: F1 (test_2020)
+    - type: precision
       value: 0.6943653955606147
-    - name: Recall (test_2020)
-      type: recall
+      name: Precision (test_2020)
+    - type: recall
       value: 0.6331084587441619
-    - name: Macro F1 (test_2020)
-      type: f1_macro
+      name: Recall (test_2020)
+    - type: f1_macro
       value: 0.6225690518125756
-    - name: Macro Precision (test_2020)
-      type: precision_macro
+      name: Macro F1 (test_2020)
+    - type: precision_macro
       value: 0.6499146769265831
-    - name: Macro Recall (test_2020)
-      type: recall_macro
+      name: Macro Precision (test_2020)
+    - type: recall_macro
       value: 0.6036807965123165
-    - name: Entity Span F1 (test_2020)
-      type: f1_entity_span
+      name: Macro Recall (test_2020)
+    - type: f1_entity_span
       value: 0.7716535433070866
-    - name: Entity Span Precision (test_2020)
-      type: precision_entity_span
+      name: Entity Span F1 (test_2020)
+    - type: precision_entity_span
       value: 0.8092255125284739
-    - name: Entity Span Recall (test_2020)
-      type: recall_entity_span
+      name: Entity Span Precision (test_2020)
+    - type: recall_entity_span
       value: 0.7374156720290607
-
-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/roberta-large-tweetner7-2020-selflabel2020-all