TinyBanglaClickbaitBERT: Distilled multi-task Bengali clickbait detection model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
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+tiny_bangla_clickbait_bert.onnx.data filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language: bn
+tags:
+  - bengali
+  - clickbait-detection
+  - knowledge-distillation
+  - tinybert
+  - multi-task
+license: mit
+---
+
+# TinyBanglaClickbaitBERT
+
+A compact Bengali clickbait detection model distilled from BanglaClickbaitBERT.
+
+## Model Details
+- **Architecture**: 4-layer Transformer (384-d, 6 heads)
+- **Parameters**: 20.1M (vs 110.2M teacher → 5.5x compression)
+- **Tasks**: Binary (clickbait/non-clickbait) + 11-class multiclass
+
+## Performance
+
+| Task | Student F1 | Teacher F1 | Retention |
+|------|-----------|-----------|-----------|
+| Binary (macro) | 0.8543 | 0.8849 | 96.5% |
+| Multiclass (macro) | 0.4201 | 0.5088 | 82.6% |
+
+## Speed
+- Teacher: 7.9 ms | Student: 3.4 ms | **2.3x speedup**
+- Teacher: 440.9 MB | Student: 80.3 MB | **5.5x compression**
+
+## Usage
+```python
+import torch
+checkpoint = torch.load("tiny_bangla_clickbait_bert.pt")
+# See label_config.json for class mappings
+```
+
+## Distilled from
+[khalidsyfullah/bangla-clickbait-multitask](https://huggingface.co/khalidsyfullah/bangla-clickbait-multitask)

best_student.pt

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label_config.json

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+{
+  "binary_classes": [
+    "clickbait",
+    "not_clickbait"
+  ],
+  "multi_classes": [
+    "analytical",
+    "celebrity_click",
+    "curiosity_gap",
+    "emotional",
+    "factual",
+    "fake_news",
+    "general",
+    "informative",
+    "misleading",
+    "reportage",
+    "sensational"
+  ],
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+  "num_binary_labels": 2,
+  "num_multi_labels": 11
+}

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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
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+}