Librarian Bot: Add base_model information to model

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

@@ -15,28 +15,30 @@ metrics:
 - precision
 - recall
 widget:
-- text: "$LOW - Lowe's racks up another positive rating despite recession risk"
-  example_title: "Bullish Sentiment"
-- text: "$HNHAF $HNHPD $AAPL - Trendforce cuts iPhone estimate after Foxconn delay"
-  example_title: "Bearish Sentiment"
-- text: "Coin Toss: Morgan Stanley Raises Tesla Bull Case To $500, Keeps Bear Case At $10"
-  example_title: "Neutral Sentiment"
+- text: $LOW - Lowe's racks up another positive rating despite recession risk
+  example_title: Bullish Sentiment
+- text: $HNHAF $HNHPD $AAPL - Trendforce cuts iPhone estimate after Foxconn delay
+  example_title: Bearish Sentiment
+- text: 'Coin Toss: Morgan Stanley Raises Tesla Bull Case To $500, Keeps Bear Case
+    At $10'
+  example_title: Neutral Sentiment
+base_model: yiyanghkust/finbert-tone
 model-index:
 - name: finbert-tone-finetuned-fintwitter-classification
   results:
   - task:
-      name: Text Classification
       type: text-classification
+      name: Text Classification
     dataset:
       name: twitter-financial-news-sentiment
       type: finance
     metrics:
     - type: F1
-      name: F1
       value: 0.8838
+      name: F1
     - type: accuracy
+      value: 0.884
       name: accuracy
-      value: 0.8840
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You