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
Framework versions
