Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`albert-large-v2`](https://huggingface.co/albert-large-v2) 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
@@ -9,35 +11,36 @@ metrics:
 - recall
 - f1
 - accuracy
-language:
-- en
 widget:
-- text: "Light dissolved inorganic carbon (DIC) resulting from the oxidation of hydrocarbons."
-- text: "RAFs are plotted for a selection of neurons in the dorsal zone (DZ) of auditory cortex in Figure 1."
-- text: "Images were acquired using a GE 3.0T MRI scanner with an upgrade for echo-planar imaging (EPI)."
+- text: Light dissolved inorganic carbon (DIC) resulting from the oxidation of hydrocarbons.
+- text: RAFs are plotted for a selection of neurons in the dorsal zone (DZ) of auditory
+    cortex in Figure 1.
+- text: Images were acquired using a GE 3.0T MRI scanner with an upgrade for echo-planar
+    imaging (EPI).
+base_model: albert-large-v2
 model-index:
 - name: albert-large-v2-finetuned-ner_with_callbacks
   results:
   - task:
-      name: Token Classification
       type: token-classification
+      name: Token Classification
     dataset:
       name: surrey-nlp/PLOD-unfiltered
       type: token-classification
       args: PLODunfiltered
     metrics:
-    - name: Precision
-      type: precision
+    - type: precision
       value: 0.9655166719570215
-    - name: Recall
-      type: recall
+      name: Precision
+    - type: recall
       value: 0.9608483288141474
-    - name: F1
-      type: f1
+      name: Recall
+    - type: f1
       value: 0.9631768437660728
-    - name: Accuracy
-      type: accuracy
+      name: F1
+    - type: accuracy
       value: 0.9589410429715819
+      name: Accuracy
 ---
 
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