Retrained with adaptive-classifier v0.0.17 (k parameter fix)

README.md

@@ -17,16 +17,16 @@ You can install it with `pip install adaptive-classifier`.
 
 - Base Model: answerdotai/ModernBERT-base
 - Number of Classes: 4
-- Total Examples: 321
+- Total Examples: 20
 - Embedding Dimension: 768
 
 ## Class Distribution
 
 ```
-books: 81 examples (25.2%)
-clothing: 80 examples (24.9%)
-electronics: 80 examples (24.9%)
-home_garden: 80 examples (24.9%)
+books: 5 examples (25.0%)
+clothing: 5 examples (25.0%)
+electronics: 5 examples (25.0%)
+home_garden: 5 examples (25.0%)
 ```
 
 ## Usage

config.json

@@ -44,5 +44,11 @@
     "home_garden": 3
   },
   "model_name": "answerdotai/ModernBERT-base",
-  "train_steps": 11
+  "train_steps": 11,
+  "training_history": {
+    "books": 100,
+    "clothing": 100,
+    "electronics": 100,
+    "home_garden": 100
+  }
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f788910ec9d2c7015d51fb712584303132ab75229723075e94fd41eee36f2f77
+oid sha256:613189e068ec6459438c5219555a7975c63882a8be76fddfe1ebd1cf27fe204c
 size 3562904