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Add pii-detection

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  1. README.md +74 -0
  2. config.json +46 -0
  3. examples.json +0 -0
  4. model.safetensors +3 -0
README.md ADDED
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+ ---
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+ language: multilingual
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+ tags:
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+ - adaptive-classifier
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+ - text-classification
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+ - continuous-learning
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+ license: apache-2.0
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+ ---
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+
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+ # Adaptive Classifier
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+
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+ This model is an instance of an [adaptive-classifier](https://github.com/codelion/adaptive-classifier) that allows for continuous learning and dynamic class addition.
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+
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+ You can install it with `pip install adaptive-classifier`.
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+
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+ ## Model Details
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+
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+ - Base Model: answerdotai/ModernBERT-base
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+ - Number of Classes: 3
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+ - Total Examples: 264
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+ - Embedding Dimension: 768
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+
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+ ## Class Distribution
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+
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+ ```
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+ contains_pii: 88 examples (33.3%)
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+ no_pii: 88 examples (33.3%)
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+ partial_pii: 88 examples (33.3%)
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+ ```
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+
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+ ## Usage
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+
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+ ```python
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+ from adaptive_classifier import AdaptiveClassifier
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+
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+ # Load the model
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+ classifier = AdaptiveClassifier.from_pretrained("adaptive-classifier/model-name")
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+
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+ # Make predictions
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+ text = "Your text here"
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+ predictions = classifier.predict(text)
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+ print(predictions) # List of (label, confidence) tuples
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+
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+ # Add new examples
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+ texts = ["Example 1", "Example 2"]
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+ labels = ["class1", "class2"]
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+ classifier.add_examples(texts, labels)
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+ ```
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+
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+ ## Training Details
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+
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+ - Training Steps: 9
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+ - Examples per Class: See distribution above
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+ - Prototype Memory: Active
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+ - Neural Adaptation: Active
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+
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+ ## Limitations
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+
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+ This model:
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+ - Requires at least 3 examples per class
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+ - Has a maximum of 150 examples per class
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+ - Updates prototypes every 10 examples
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @software{adaptive_classifier,
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+ title = {Adaptive Classifier: Dynamic Text Classification with Continuous Learning},
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+ author = {Sharma, Asankhaya},
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+ year = {2025},
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+ publisher = {GitHub},
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+ url = {https://github.com/codelion/adaptive-classifier}
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+ }
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+ ```
config.json ADDED
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+ {
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+ "config": {
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+ "batch_size": 16,
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+ "cost_coefficients": {},
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+ "cost_function_type": "separable",
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+ "device_map": "auto",
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+ "early_stopping_patience": 3,
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+ "enable_strategic_mode": false,
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+ "epochs": 10,
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+ "ewc_lambda": 100.0,
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+ "gradient_checkpointing": false,
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+ "learning_rate": 2e-05,
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+ "max_examples_per_class": 150,
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+ "max_length": 512,
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+ "min_confidence": 0.1,
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+ "min_examples_per_class": 3,
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+ "neural_weight": 0.4,
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+ "num_representative_examples": 5,
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+ "prototype_update_frequency": 10,
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+ "prototype_weight": 0.6,
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+ "quantization": null,
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+ "similarity_threshold": 0.7,
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+ "strategic_blend_regular_weight": 0.6,
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+ "strategic_blend_strategic_weight": 0.4,
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+ "strategic_lambda": 0.1,
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+ "strategic_prediction_head_weight": 0.5,
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+ "strategic_prediction_proto_weight": 0.5,
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+ "strategic_robust_head_weight": 0.2,
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+ "strategic_robust_proto_weight": 0.8,
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+ "strategic_training_frequency": 10,
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+ "warmup_steps": 0
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+ },
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+ "embedding_dim": 768,
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+ "id_to_label": {
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+ "0": "no_pii",
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+ "1": "contains_pii",
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+ "2": "partial_pii"
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+ },
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+ "label_to_id": {
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+ "contains_pii": 1,
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+ "no_pii": 0,
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+ "partial_pii": 2
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+ },
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+ "model_name": "answerdotai/ModernBERT-base",
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+ "train_steps": 9
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+ }
examples.json ADDED
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model.safetensors ADDED
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