Training Run
- Run identifier:
301143e0
- Base model:
meta-llama/Llama-4-Scout-17B-16E-Instruct
- Export base path in adapter config:
togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit
- Training method: SFT
- Adapter type: LoRA
- Data format: chat/instruction
- Epochs: 3
- Global steps: 489
- LoRA rank: 32
- LoRA alpha: 64
- Final exported eval loss: 1.072265625
Dataset
This run was trained after expanding the dataset through Adaption Labs with additional domain-specific and general-purpose datapoints.
The task is DeFi wallet risk classification from behavioral feature prompts, including signals such as transaction count, action ratios, asset concentration, protocol concentration, data quality, and wallet profile.
Important: these labels are retrospective proxy labels for hackathon model development. They should not be described as production-verified liquidation, loss, or drawdown events.
Intended Use
This adapter is intended for research and demonstration around DeFi wallet risk classification. It can support decision-support workflows where model output is presented as a risk-review signal, not as financial advice.
Files
adapter_model.safetensorsadapter_config.jsontokenizer.jsontokenizer_config.jsonspecial_tokens_map.jsonchat_template.jinjatrainer_state.json
License And Base Model Terms
Use of this adapter is subject to the license and acceptable-use terms of the base model, Hugging Face, and Adaption Labs challenge requirements.