Adaption Market Analysis Final Model

This repository contains the PEFT LoRA adapter produced in Attempt 2 of our AutoScientist Challenge project. The model was adapted for analyst-style finance responses using the 45,758-row Final dataset created with Adaption Labs' Adaptive Data and Combine workflows.

Artifact

Base model: togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit
Adapter type: LoRA for causal language modeling
Rank: 32
Alpha: 64
Dropout: 0.05
Target modules: q_proj, k_proj, v_proj, o_proj
Training: 2 epochs, 168 steps, peak learning rate 2e-5
Run ID: adaption_llama_4_scout_17b_16_final_cc7ddeac

This is an adapter, not a standalone merged model. Load it with PEFT on top of the declared base model and its compatible tokenizer configuration.

Training data

The combined dataset contains 45,758 rows spanning company, fund, macro, fixed-income, and real-estate analysis. Its Adaption data-quality grade improved from B to A.

Evaluation

In Adaption's dataset-specific pairwise preference evaluation, the adapted model was preferred 80 to 20 over the base model. This is a preference result, not an accuracy score. Attempt 2 did not produce a Market Analysis category evaluation, so this result does not establish external-domain transfer.

Limitations

The adapter inherits the capabilities, restrictions, and risks of its base model.
The evaluation is dataset-specific and should not be read as investment accuracy.
Outputs are not financial advice and require human review before real-world use.
The complete AutoScientist runtime configuration was not exported; this release records the adapter configuration and trainer state included with the run.

Project

Write-up: https://adaptions-writeup.vercel.app/
Repository: https://github.com/Kitkitkittt/AdaptMarket
Authors: Keith Vo and Huy X. Dang

Framework versions

PEFT 0.15.1

Downloads last month: -

Model tree for huyxdang/adaption-market-analysis-final-model

Base model

togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit

Adapter

(10)

this model