learnfinance-models-sac

hajirazin/learnfinance-models-sac

learnfinance-models-sac is a reinforcement learning model from hajirazin. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.

SAC v3 masked-attention portfolio allocator with ranked stock tokens.

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.pt169 KB · 94%

At a glance

Task: Reinforcement Learning
Access: Public
Created: Jan 30, 2026
Updated: Oct 4, 2026
SHA: fc0924e1

Model card

From the Hugging Face model README

LearnFinance SAC Model - v2026-10-02_4e5831c9

SAC v3 masked-attention portfolio allocator with ranked stock tokens.

Model Details

Version: v2026-10-02_4e5831c9
Model Type: SAC v3 (masked attention, 30 stock slots + CASH)
Training Window: 2016-01-01 to 2026-10-02
Symbols: 15 stocks

Components

actor.pt - Gaussian policy network
critic.pt - Twin Q-value networks
critic_target.pt - Target Q-value networks
log_alpha.pt - Entropy temperature coefficient
scaler.pkl - PortfolioScaler for state normalization
symbol_order.json - Ordered list of portfolio symbols
metadata.json - SAC v3 schema, architecture, slot map, and audit metadata
sac_v3_auxiliary.json - HMM parameters/scaler/labels, causal cutoff state, and market tail

Metrics

Actor Loss: 0.7087951302528381
Critic Loss: 0.3011290431022644
Avg Episode Return: 0.2680437052841098
Avg Episode Sharpe: 0.16980871650842833
Eval Sharpe: 1.744801662301668
Eval CAGR: 0.5650465767056425
Eval Max Drawdown: 0.18415490988733238

Usage

from brain_api.storage.sac import SACHuggingFaceModelStorage
from brain_api.storage.sac.local import SACHalalFilteredModelStorage

storage = SACHuggingFaceModelStorage(
    repo_id="hajirazin/learnfinance-models-sac",
    local_cache=SACHalalFilteredModelStorage(),
)
artifacts = storage.download_model(version="v2026-10-02_4e5831c9")

Task: Reinforcement Learning
Created: Jan 30, 2026
Updated: Oct 4, 2026