Add risk-assessment

README.md

@@ -16,17 +16,15 @@ You can install it with `pip install adaptive-classifier`.
 ## Model Details
 
 - Base Model: answerdotai/ModernBERT-base
-- Number of Classes: 4
-- Total Examples: 20
+- Number of Classes: 2
+- Total Examples: 160
 - Embedding Dimension: 768
 
 ## Class Distribution
 
 ```
-high_risk: 5 examples (25.0%)
-low_risk: 5 examples (25.0%)
-medium_risk: 5 examples (25.0%)
-minimal_risk: 5 examples (25.0%)
+high_risk: 80 examples (50.0%)
+low_risk: 80 examples (50.0%)
 ```
 
 ## Usage
@@ -50,7 +48,7 @@ classifier.add_examples(texts, labels)
 
 ## Training Details
 
-- Training Steps: 10
+- Training Steps: 5
 - Examples per Class: See distribution above
 - Prototype Memory: Active
 - Neural Adaptation: Active

config.json

@@ -32,17 +32,13 @@
   },
   "embedding_dim": 768,
   "id_to_label": {
-    "0": "minimal_risk",
-    "1": "high_risk",
-    "2": "low_risk",
-    "3": "medium_risk"
+    "0": "low_risk",
+    "1": "high_risk"
   },
   "label_to_id": {
     "high_risk": 1,
-    "low_risk": 2,
-    "medium_risk": 3,
-    "minimal_risk": 0
+    "low_risk": 0
   },
   "model_name": "answerdotai/ModernBERT-base",
-  "train_steps": 10
+  "train_steps": 5
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:11de6da3346f2d7c9550cfb48aebf51dca04d274b999df7170eab40625051cec
-size 3562912
+oid sha256:fa335e2d40ddb6f53aeeec1d66c761c79545d93c6f129a036fb2932be90c2ff8
+size 3553512