Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`microsoft/swin-tiny-patch4-window7-224`](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) 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).

If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co./librarian-bot) [Metadata Request Service](https://huggingface.co./spaces/librarian-bots/metadata_request_service)!

README.md

@@ -7,20 +7,21 @@ datasets:
 - lewtun/dog_food
 metrics:
 - accuracy
+base_model: microsoft/swin-tiny-patch4-window7-224
 model-index:
 - name: swin-tiny-finetuned-dogfood
   results:
   - task:
-      name: Image Classification
       type: image-classification
+      name: Image Classification
     dataset:
       name: lewtun/dog_food
       type: lewtun/dog_food
       args: lewtun--dog_food
     metrics:
-    - name: Accuracy
-      type: accuracy
+    - type: accuracy
       value: 0.988
+      name: Accuracy
   - task:
       type: image-classification
       name: Image Classification
@@ -30,53 +31,53 @@ model-index:
       config: lewtun--dog_food
       split: test
     metrics:
-    - name: Accuracy
-      type: accuracy
+    - type: accuracy
       value: 0.9826666666666667
+      name: Accuracy
       verified: true
-    - name: Precision Macro
-      type: precision
+    - type: precision
       value: 0.9820904286553143
+      name: Precision Macro
       verified: true
-    - name: Precision Micro
-      type: precision
+    - type: precision
       value: 0.9826666666666667
+      name: Precision Micro
       verified: true
-    - name: Precision Weighted
-      type: precision
+    - type: precision
       value: 0.9828416519866903
+      name: Precision Weighted
       verified: true
-    - name: Recall Macro
-      type: recall
+    - type: recall
       value: 0.9828453314981092
+      name: Recall Macro
       verified: true
-    - name: Recall Micro
-      type: recall
+    - type: recall
       value: 0.9826666666666667
+      name: Recall Micro
       verified: true
-    - name: Recall Weighted
-      type: recall
+    - type: recall
       value: 0.9826666666666667
+      name: Recall Weighted
       verified: true
-    - name: F1 Macro
-      type: f1
+    - type: f1
       value: 0.9824101123169301
+      name: F1 Macro
       verified: true
-    - name: F1 Micro
-      type: f1
+    - type: f1
       value: 0.9826666666666667
+      name: F1 Micro
       verified: true
-    - name: F1 Weighted
-      type: f1
+    - type: f1
       value: 0.9826983433609648
+      name: F1 Weighted
       verified: true
-    - name: loss
-      type: loss
+    - type: loss
       value: 0.2326570302248001
+      name: loss
       verified: true
-    - name: matthews_correlation
-      type: matthews_correlation
+    - type: matthews_correlation
       value: 0.974016655798285
+      name: matthews_correlation
       verified: true
 ---