Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`Visual-Attention-Network/van-base`](https://huggingface.co/Visual-Attention-Network/van-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: apache-2.0
 tags:
 - generated_from_trainer
@@ -7,12 +9,14 @@ metrics:
 - f1
 - recall
 - precision
+pipeline_tag: image-classification
+base_model: Visual-Attention-Network/van-base
 model-index:
 - name: van-base-Brain_Tumors_Image_Classification
   results:
   - task:
-      name: Image Classification
       type: image-classification
+      name: Image Classification
     dataset:
       name: imagefolder
       type: imagefolder
@@ -20,12 +24,9 @@ model-index:
       split: train
       args: default
     metrics:
-    - name: Accuracy
-      type: accuracy
+    - type: accuracy
       value: 0.7918781725888325
-language:
-- en
-pipeline_tag: image-classification
+      name: Accuracy
 ---
 
 <h1>van-base-Brain_Tumors_Image_Classification</h1>