Abhayn01/arka-advanced-slm-sft-v1

ARKA Advanced SLM — Mixed SFT v1

ARKA stands for Academic Research Knowledge Assistant.

Creator/developer: Abhay Kumar Rudrapaul.

Base

Abhayn01/arka-advanced-slm-scitech-stream-500m-v1

Architecture / lineage information

• —Decoder-only causal language model
• —Approximately 124.4M parameters
• —GPT-2 tokenizer vocabulary: 50,257
• —Context length used for this SFT: 1024
• —Full-model SFT; transformer layers were not frozen
• —SFT learning rate: 5e-06

SFT mixture

• —MMLU auxiliary training questions
• —SQuAD 2.0
• —OpenBookQA
• —AI2 ARC Challenge and Easy
• —SciQ
• —CounterFact factual/counterfactual relations (true target is supervised; false target is never used as the answer)
• —ARKA identity/model information
• —Creator profile examples explicitly requested by the creator
• —ChatML-style, Alpaca-style, QA, and context-guided serializations

Train examples: 160,863 Validation examples: 4,000

Creator profile included by request

• —Name: Abhay Kumar Rudrapaul
• —B.Tech in Electrical Engineering
• —Tripura Institute of Technology, Narsingarh
• —Agartala, Tripura, India
• —Interests include AI, machine learning, technology, language-model development, and applied AI systems
• —Creator/developer of ARKA and TIT Campus Assistant–ARKA

No passwords, account credentials, private IDs, or health information are included.

Notes

The GPT-2 tokenizer vocabulary is kept unchanged. ChatML markers are learned as ordinary text sequences rather than adding new tokenizer special tokens.

Review each upstream dataset's license/terms before redistributing transformed data. This model repository records the source names but does not upload transformed copies of those source datasets.