Upload from benchmark script
Browse files- README.md +73 -0
- config.json +33 -0
- examples.json +0 -0
- model.safetensors +3 -0
README.md
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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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# Adaptive Classifier
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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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You can install it with `pip install adaptive-classifier`.
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## Model Details
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- Base Model: distilbert/distilbert-base-cased
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- Number of Classes: 2
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- Total Examples: 616
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- Embedding Dimension: 768
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## Class Distribution
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```
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HIGH: 308 examples (50.0%)
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LOW: 308 examples (50.0%)
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```
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## Usage
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```python
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from adaptive_classifier import AdaptiveClassifier
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# Load the model
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classifier = AdaptiveClassifier.from_pretrained("distilbert/distilbert-base-cased")
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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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# 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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## Training Details
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- Training Steps: 20
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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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## Limitations
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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 500 examples per class
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- Updates prototypes every 50 examples
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## Citation
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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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```
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config.json
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{
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"config": {
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"batch_size": 32,
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"device_map": "auto",
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"early_stopping_patience": 3,
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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": 0.0005,
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"max_examples_per_class": 500,
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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": 0.2,
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"num_representative_examples": 5,
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"prototype_update_frequency": 50,
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"prototype_weight": 0.8,
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"quantization": null,
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"similarity_threshold": 0.7,
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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": "HIGH",
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"1": "LOW"
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},
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"label_to_id": {
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"HIGH": 0,
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"LOW": 1
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},
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"model_name": "distilbert/distilbert-base-cased",
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"train_steps": 20
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}
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examples.json
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d35ab846d8a61c801b3fa4f6dd184469445035e51c9ba6b823ae2704d147c86e
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size 3553504
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