Librarian Bot: Add base_model information to model

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

@@ -1,7 +1,16 @@
 ---
+language:
+- pt
 license: mit
 tags:
 - generated_from_keras_callback
+datasets:
+- assin2
+metrics:
+- accuracy
+- f1
+pipeline_tag: text-classification
+base_model: neuralmind/bert-base-portuguese-cased
 model-index:
 - name: pmfsl/bertimbau-base-finetuned-rte
   results:
@@ -9,21 +18,13 @@ model-index:
       type: text-classification
       name: Natural Lenguage Inference
     dataset:
-      type: assin2
       name: ASSIN2
+      type: assin2
     metrics:
     - type: accuracy
       value: 0.877859477124183
     - type: f1
       value: 0.8860083873427372
-datasets:
-- assin2
-metrics:
-- accuracy
-- f1
-language:
-- pt
-pipeline_tag: text-classification
 ---
 
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