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Glossary
DistilBERT — A smaller pretrained bidirectional Transformer encoder used here for text classification.
Fine-tuning — Updating pretrained model weights on a new supervised task.
Frozen backbone — Holding the pretrained encoder's parameters constant while updating the classification head.
SFT — Supervised Fine-Tuning on input/target responses.
DPO — Direct Preference Optimization using preferred and dispreferred responses, generally relative to a reference policy.
LoRA — Low-Rank Adaptation, a parameter-efficient method for training adapter matrices.
NF4 — NormalFloat 4-bit representation used in some model-quantization training pipelines.
ORPO — Odds Ratio Preference Optimization; included only as draft sample text in this project.
PPO — Proximal Policy Optimization; not implemented in this repository.
HLD / LLD — High-Level Design and Low-Level Design architectural documents.
Transformer Training Wiki · Implementation status: DistilBERT source available.This project is licensed under the Apache License, Version 2.0.© 2026 Sudhanshu Shukla · Licensed under the Apache License, Version 2.0
Overview
Architecture
Implemented classifier
- DistilBERT-Workflow
- Dataset-and-Labels
- Training-Configuration
- Evaluation-and-Inference
- Frozen-Backbone-Comparison
- Artifacts-and-Checkpoints
Experimental alignment draft
Operations