Reinforce
reinforce-ada-raw-eval
Reinforce-Ada Raw Eval
Raw evaluation artifacts organized by experiment / dataset / step.
Included files when present:
merged_data.jsonl
pass_at_k.json
record.txt
Experiments: grpo_n8, grpo_n16, grpo_n32, reinforce_ada_n8, reinforce_ada_n8_normstdtrue
Datasets: math500, minerva_math, olympiadbench, aime_hmmt_brumo_cmimc_amc23
vehicular-traffic-light-reinforcementMulti-Agent_Reinforcement_Learning_Trading_System_Data
📊 Multi-Agent RL Trading System - Dataset
This dataset contains historical OHLCV (Open, High, Low, Close, Volume) data for AAPL, MSFT, and GOOGL, pre-processed for Reinforcement Learning based trading systems.
📁 Dataset Content
The dataset consists of CSV files downloaded via yfinance:
AAPL.csv: Apple Inc. daily data (Jan 2018 - Dec 2024).
MSFT.csv: Microsoft Corp. daily data (Jan 2018 - Dec 2024).
GOOGL.csv: Alphabet Inc. daily data (Jan 2018 - Dec 2024).
📝… See the full description on the dataset page: https://huggingface.co/datasets/AdityaaXD/Multi-Agent_Reinforcement_Learning_Trading_System_Data.reinforce-ada-eval-t07
Reinforce-Ada Eval t=0.7
Evaluation artifacts for temperature 0.7, K=64, PASS_K_MAX=64.
Experiments:
grpo_n8
reinforce_ada_n8
Per step / dataset directory contains:
merged_data.jsonl
pass_at_k.json
record.txt
Original outputs were written under global_step_xxx/merged/weqweasdas/*__t07_k64 and remapped into this repo.
reinforce-ada-n16
Reinforce-Ada n16 Eval Artifacts
Evaluation artifacts for reinforce_ada_n16_mr4_rr16.
Included eval suffixes:
t07_k64: steps [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000]
t10_k64: steps [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000]
Each step / dataset directory contains:
merged_data.jsonl
pass_at_k.json
record.txt
Multi-Agent_Reinforcement_Learning_Trading_System_Data
📊 Multi-Agent RL Trading System - Dataset
This dataset contains historical OHLCV (Open, High, Low, Close, Volume) data for AAPL, MSFT, and GOOGL, pre-processed for Reinforcement Learning based trading systems.
📁 Dataset Content
The dataset consists of CSV files downloaded via yfinance:
AAPL.csv: Apple Inc. daily data (Jan 2018 - Dec 2024).
MSFT.csv: Microsoft Corp. daily data (Jan 2018 - Dec 2024).
GOOGL.csv: Alphabet Inc. daily data (Jan 2018 - Dec 2024).… See the full description on the dataset page: https://huggingface.co/datasets/sanjaydoss/Multi-Agent_Reinforcement_Learning_Trading_System_Data.