Update README.md

README.md

@@ -1,5 +1,14 @@
 ---
-{}
+license: mit
+datasets:
+- rungalileo/ragbench
+language:
+- en
+metrics:
+- f1
+base_model:
+- answerdotai/ModernBERT-base
+pipeline_tag: text-classification
 ---
 # chiliground-base-modernbert-v1
 
@@ -9,8 +18,6 @@ A sentence classification model for extracting relevant spans from documents bas
 - Base model: answerdotai/ModernBERT-base
 - Hidden dimension: 768
 - Number of labels: 2
-- Best validation F1: 0.7038
-- Saved on: 2025-03-29 19:17:14
 
 ## Usage
 
@@ -29,19 +36,34 @@ extractor = ModelSpanExtractor(
 # Create documents
 documents = [
     Document(
-        content="Climate change is a significant issue. Rising sea levels threaten coastal areas.",
-        metadata={"source": "example"}
-    )
+        content="""
+        Climate change is a significant and lasting change in the statistical distribution of weather patterns.
+        Global warming is the observed increase in the average temperature of the Earth's atmosphere and oceans.
+        Greenhouse gases include water vapor, carbon dioxide, methane, nitrous oxide, and ozone.
+        Human activities since the beginning of the Industrial Revolution have increased greenhouse gas levels.
+        """,
+        metadata={"source": "example_doc_1", "id": "climate_1"},
+    ),
+    Document(
+        content="""
+        Renewable energy comes from sources that are naturally replenished on a human timescale.
+        Solar power is the conversion of energy from sunlight into electricity.
+        Wind power is the use of wind to provide mechanical power or electricity.
+        Hydropower is electricity generated from the energy of falling water.
+        """,
+        metadata={"source": "example_doc_2", "id": "energy_1"},
+    ),
 ]
 
+
 # Extract relevant spans
-question = "What are the effects of climate change?"
+question = "What causes climate change?""
 results = extractor.extract_spans(question, documents)
 
 # Print the results
 for doc_content, spans in results.items():
     for span in spans:
-        print(f"- {span}")
+        print(span)
 ```
 
 ## Training Data
@@ -52,4 +74,4 @@ This model was trained on a QA dataset to classify sentences as relevant or not
 
 - The model works at the sentence level and may miss relevant spans that cross sentence boundaries
 - Performance depends on the quality and relevance of the training data
-- The model is designed for English text only
+- The model is designed for English text only