Update README.md

README.md

@@ -2,9 +2,28 @@
 language:
 - en
 widget:
-- text: "We explores the impact of initial and boundary conditions on simulating an extra-tropical cyclones in the North Atlantic Ocean, employing the Weather Research and Forecasting (WRF) model. The study assesses cyclone trajectory and synoptic patterns against real-world observations, finding that the WRF model effectively replicates Gong's entire lifecycle, including its intensification phase. It was observed that both the genesis of the cyclone and its Q-Vector—a meteorological vector that indicates the potential for cyclogenesis—are significantly influenced by the initial conditions set in the model."
-  example_title: "LABEL_15 (Severe Storms)"
+- text: >-
+    We explore the impact of initial and boundary conditions on simulating an
+    extra-tropical cyclones in the North Atlantic Ocean, employing the Weather
+    Research and Forecasting (WRF) model. The study assesses cyclone trajectory
+    and synoptic patterns against real-world observations, finding that the WRF
+    model effectively replicates Gong's entire lifecycle, including its
+    intensification phase. It was observed that both the genesis of the cyclone
+    and its Q-Vector—a meteorological vector that indicates the potential for
+    cyclogenesis—are significantly influenced by the initial conditions set in
+    the model.
+  example_title: LABEL_15 (Severe Storms)
+license: cc-by-4.0
+pipeline_tag: text-classification
+tags:
+- NASA
+- GES-DISC
+- Earth Sciences
 ---
+## Model Information
+
+This model is based on the `nasa-impact/nasa-smd-ibm-st-v2` model. It has been fine-tuned for a classification task using approximately 1400 publication abstracts in earth sciences. The model was validated on 1000 unseen abstracts. The labelling of the publications was conducted by the NASA GES-DISC science team. The training and validation dataset, along with performance scores, will be published here soon.
+
 ## Label Mapping
 
 The model classifies inputs into the following categories, each represented by a unique label ID:
@@ -31,5 +50,4 @@ The model classifies inputs into the following categories, each represented by a
 | Validation                         | 17 |
 | Volcanic Eruptions                 | 18 |
 | Water Quality                      | 19 |
-| Wildfires                          | 20 |
-
+| Wildfires                          | 20 |