Add document-quality

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: 320
+- Number of Classes: 2
+- Total Examples: 163
 - Embedding Dimension: 768
 
 ## Class Distribution
 
 ```
-complete: 80 examples (25.0%)
-incomplete: 80 examples (25.0%)
-needs_review: 80 examples (25.0%)
-poor_quality: 80 examples (25.0%)
+high_quality: 80 examples (49.1%)
+poor_quality: 83 examples (50.9%)
 ```
 
 ## Usage
@@ -50,7 +48,7 @@ classifier.add_examples(texts, labels)
 
 ## Training Details
 
-- Training Steps: 10
+- Training Steps: 6
 - 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": "complete",
-    "1": "incomplete",
-    "2": "needs_review",
-    "3": "poor_quality"
+    "0": "poor_quality",
+    "1": "high_quality"
   },
   "label_to_id": {
-    "complete": 0,
-    "incomplete": 1,
-    "needs_review": 2,
-    "poor_quality": 3
+    "high_quality": 1,
+    "poor_quality": 0
   },
   "model_name": "answerdotai/ModernBERT-base",
-  "train_steps": 10
+  "train_steps": 6
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:71bb6406bd6cd22e79f776a953ddf532b133494b48080784e0d76e23d5f21053
-size 3562912
+oid sha256:f212d6310683eb27ac5e11350d6b2e067c46196008e7a2e1dfdd319c3982c09a
+size 3553520