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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: Goader/modern-liberta-large |
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- Number of Classes: 39 |
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- Total Examples: 2904 |
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- Embedding Dimension: 1024 |
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## Class Distribution |
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``` |
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0: 474 examples (16.3%) |
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1: 2 examples (0.1%) |
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2: 56 examples (1.9%) |
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3: 1 examples (0.0%) |
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4: 79 examples (2.7%) |
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5: 26 examples (0.9%) |
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6: 53 examples (1.8%) |
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7: 59 examples (2.0%) |
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8: 82 examples (2.8%) |
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9: 18 examples (0.6%) |
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10: 33 examples (1.1%) |
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11: 34 examples (1.2%) |
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12: 107 examples (3.7%) |
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13: 123 examples (4.2%) |
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14: 400 examples (13.8%) |
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15: 124 examples (4.3%) |
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16: 63 examples (2.2%) |
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17: 24 examples (0.8%) |
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18: 1 examples (0.0%) |
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19: 142 examples (4.9%) |
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20: 150 examples (5.2%) |
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21: 4 examples (0.1%) |
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22: 7 examples (0.2%) |
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23: 62 examples (2.1%) |
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24: 36 examples (1.2%) |
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25: 27 examples (0.9%) |
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26: 80 examples (2.8%) |
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27: 89 examples (3.1%) |
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28: 4 examples (0.1%) |
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29: 15 examples (0.5%) |
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30: 117 examples (4.0%) |
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31: 48 examples (1.7%) |
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32: 7 examples (0.2%) |
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33: 1 examples (0.0%) |
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34: 237 examples (8.2%) |
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35: 2 examples (0.1%) |
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36: 9 examples (0.3%) |
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37: 10 examples (0.3%) |
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38: 98 examples (3.4%) |
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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("adaptive-classifier/model-name") |
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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: 1 |
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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 1000 examples per class |
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- Updates prototypes every 100 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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