Add customer-intent

README.md

@@ -16,19 +16,17 @@ You can install it with `pip install adaptive-classifier`.
 ## Model Details
 
 - Base Model: answerdotai/ModernBERT-base
-- Number of Classes: 6
-- Total Examples: 480
+- Number of Classes: 4
+- Total Examples: 324
 - Embedding Dimension: 768
 
 ## Class Distribution
 
 ```
-cancellation: 80 examples (16.7%)
-complaint: 80 examples (16.7%)
-information: 80 examples (16.7%)
-purchase: 80 examples (16.7%)
-support: 80 examples (16.7%)
-upgrade: 80 examples (16.7%)
+complaint: 81 examples (25.0%)
+information: 80 examples (24.7%)
+purchase: 82 examples (25.3%)
+support: 81 examples (25.0%)
 ```
 
 ## Usage
@@ -52,7 +50,7 @@ classifier.add_examples(texts, labels)
 
 ## Training Details
 
-- Training Steps: 15
+- Training Steps: 11
 - Examples per Class: See distribution above
 - Prototype Memory: Active
 - Neural Adaptation: Active

config.json

@@ -32,21 +32,17 @@
   },
   "embedding_dim": 768,
   "id_to_label": {
-    "0": "complaint",
-    "1": "cancellation",
-    "2": "purchase",
-    "3": "information",
-    "4": "support",
-    "5": "upgrade"
+    "0": "support",
+    "1": "purchase",
+    "2": "information",
+    "3": "complaint"
   },
   "label_to_id": {
-    "cancellation": 1,
-    "complaint": 0,
-    "information": 3,
-    "purchase": 2,
-    "support": 4,
-    "upgrade": 5
+    "complaint": 3,
+    "information": 2,
+    "purchase": 1,
+    "support": 0
   },
   "model_name": "answerdotai/ModernBERT-base",
-  "train_steps": 15
+  "train_steps": 11
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:29b14288d0ecd18bd17419951a2896b2112e4070e67546069818e5af87771dc7
-size 3572304
+oid sha256:fd5b5f49c44a70e89a96e58d1a80b760b864d5f0c428d83cb11b030d7b12773a
+size 3562904