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README.md

@@ -1,22 +1,18 @@
 ---
 language: en
 tags: [text-classification, emotion-detection, mental-health, hci, distilbert, cnn]
-datasets: [dair-ai/emotion]
+datasets: [go_emotions]
 metrics: [f1, accuracy]
 ---
 # MoodShift — Hybrid DistilBERT + CNN Emotion Classifier
 Novel hybrid architecture for HCI research (ICCA 2026).
 
 ## Architecture
-
 - **DistilBERT** → [CLS] global context (768-dim)
-
-- **CNN (kernels 2,3,4)** → local n-gram patterns (384-dim)
-
-- **Fusion** → 1152-dim → Linear(512) → Linear(6)
+- **CNN (kernels 2,3,4)** → local n-gram emotion patterns (384-dim)
+- **Fusion** → 1152-dim → Linear(512) → Linear(7)
 
 ## Labels
+positive | sadness | anger | anxiety | confusion | curiosity | neutral
 
-sadness | joy | love | anger | fear | surprise
-
-Best Val F1: **0.9239**
+Best Val F1: **0.9141**

config.json

@@ -26,5 +26,5 @@
   ],
   "max_len": 128,
   "bert_base": "distilbert-base-uncased",
-  "best_val_f1": 0.9239
+  "best_val_f1": 0.9141
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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 size 284087647

tokenizer.json

@@ -1,21 +1,7 @@
 {
   "version": "1.0",
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-    "pad_to_multiple_of": null,
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-    "pad_type_id": 0,
-    "pad_token": "[PAD]"
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   "added_tokens": [
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