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Quantum-Clasifier-Finetuned
Fine-tuned version of:
Nebulixlabs/Quantum-Classifier
Architecture
- Parameters: 1,000,000
- Vocabulary: 4096
- Context length: 128
- Hidden size: 112
- Attention heads: 7
- Transformer layers: 4
- FFN: 336
- Classifier hidden: 170
Fine-tuning
Datasets:
- Nebulixlabs/safety-dataset
- KimDongH/spam_dataset-train-eval-test2
Batch size:
128
Target tokens:
30,000,000
Actual tokens:
30,010,756
Epochs:
9
Labels
0 = safe
1 = unsafe
Confidence
Temperature calibrated on validation data:
1.479935
Evaluation
The held-out test split, where available, is evaluated only after fine-tuning.
Multilingual smoke tests cover:
- English
- Hindi
- Hinglish
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