Librarian Bot: Add base_model information to model

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

@@ -1,30 +1,31 @@
 ---
+language:
+- en
 license: apache-2.0
 tags:
 - generated_from_trainer
 - nlu
 - text-classification
+datasets:
+- AmazonScience/massive
 metrics:
 - accuracy
 - f1
+base_model: bert-base-uncased
 model-index:
 - name: bert-base-uncased-amazon-massive-intent
   results:
   - task:
-      name: intent-classification
       type: intent-classification
+      name: intent-classification
     dataset:
       name: MASSIVE
       type: AmazonScience/massive
       split: test
     metrics:
-    - name: F1
-      type: f1
+    - type: f1
       value: 0.8903
-datasets:
-- AmazonScience/massive
-language:
-- en
+      name: F1
 ---
 
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