From dc801c07cf38b0c495686463e6ca6f871a64440e Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Tue, 27 Jan 2026 09:57:37 -0600 Subject: Add collaborativeagents module and update gitignore - Add collaborativeagents subproject with adapters, agents, and evaluation modules - Update .gitignore to exclude large binary files (.whl, .tar), wandb logs, and results Co-Authored-By: Claude Opus 4.5 --- collaborativeagents/slurm/run_grpo_training.sh | 69 ++++++++++++++++++++++++++ 1 file changed, 69 insertions(+) create mode 100755 collaborativeagents/slurm/run_grpo_training.sh (limited to 'collaborativeagents/slurm/run_grpo_training.sh') diff --git a/collaborativeagents/slurm/run_grpo_training.sh b/collaborativeagents/slurm/run_grpo_training.sh new file mode 100755 index 0000000..4f9e3f1 --- /dev/null +++ b/collaborativeagents/slurm/run_grpo_training.sh @@ -0,0 +1,69 @@ +#!/bin/bash +#SBATCH --job-name=grpo_refl +#SBATCH --account=bfqt-delta-gpu +#SBATCH --partition=gpuA100x4 +#SBATCH --nodes=1 +#SBATCH --ntasks=1 +#SBATCH --cpus-per-task=16 +#SBATCH --gres=gpu:4 +#SBATCH --mem=200G +#SBATCH --time=48:00:00 +#SBATCH --output=logs/grpo_reflection_%j.out +#SBATCH --error=logs/grpo_reflection_%j.err + +set -e +cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model +mkdir -p collaborativeagents/slurm/logs collaborativeagents/training/outputs + +source /u/yurenh2/miniforge3/etc/profile.d/conda.sh +conda activate eval + +export HF_HOME=/projects/bfqt/users/yurenh2/hf_cache/huggingface +export PYTHONPATH="${PWD}/src:${PWD}/collaborativeagents:${PYTHONPATH}" +export NCCL_P2P_DISABLE=1 + +# Use the AWQ 70B model for judge (fits on 2 GPUs) +JUDGE_MODEL="hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4" +JUDGE_PORT=8000 + +# Start vLLM server for judge model (on GPUs 2,3) +echo "=== Starting vLLM judge server ===" +CUDA_VISIBLE_DEVICES=2,3 python -m vllm.entrypoints.openai.api_server \ + --model "$JUDGE_MODEL" \ + --port $JUDGE_PORT \ + --tensor-parallel-size 2 \ + --max-model-len 8192 \ + --dtype auto \ + --trust-remote-code & + +VLLM_PID=$! +echo "vLLM server PID: $VLLM_PID" + +# Wait for server to be ready +echo "Waiting for vLLM server to start..." +for i in {1..60}; do + if curl -s http://localhost:$JUDGE_PORT/health > /dev/null 2>&1; then + echo "vLLM server is ready!" + break + fi + sleep 10 +done + +# Run GRPO training (on GPUs 0,1) +echo "=== Starting GRPO training ===" +CUDA_VISIBLE_DEVICES=0,1 python collaborativeagents/training/train_grpo.py \ + --model-path collaborativeagents/training/outputs/sft_reflection \ + --data-path collaborativeagents/training/training_data/grpo_training_data.json \ + --output-dir collaborativeagents/training/outputs/grpo_reflection \ + --judge-url "http://localhost:$JUDGE_PORT/v1" \ + --judge-model "$JUDGE_MODEL" \ + --max-steps 200 \ + --learning-rate 1e-6 \ + --num-generations 8 + +# Cleanup +echo "=== Cleanup ===" +kill $VLLM_PID 2>/dev/null || true + +echo "=== GRPO Training Complete ===" +echo "Model saved to: collaborativeagents/training/outputs/grpo_reflection/final" -- cgit v1.2.3