Librarian Bot: Add base_model information to model

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

@@ -1,4 +1,6 @@
 ---
+language:
+- en
 license: cc-by-sa-4.0
 tags:
 - financial-sentiment-analysis
@@ -19,31 +21,29 @@ metrics:
 widget:
 - text: The USD rallied by 10% last night
   example_title: Bullish Sentiment
-- text: >-
-    Covid-19 cases have been increasing over the past few months impacting
-    earnings for global firms
+- text: Covid-19 cases have been increasing over the past few months impacting earnings
+    for global firms
   example_title: Bearish Sentiment
 - text: the USD has been trending lower
   example_title: Mildly Bearish Sentiment
+base_model: nlpaueb/sec-bert-base
 model-index:
 - name: sec-bert-finetuned-finance-classification
   results:
   - task:
-      name: Text Classification
       type: text-classification
+      name: Text Classification
     dataset:
       name: financial_phrasebank
       type: finance
       args: sentence_50agree
     metrics:
     - type: F1
-      name: F1
       value: 0.8744
+      name: F1
     - type: accuracy
-      name: accuracy
       value: 0.8755
-language:
-- en
+      name: accuracy
 ---
 
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