experiments/slurm/run_pub_multiseed_exp1.sh

#!/bin/bash
#SBATCH --partition=gpuA800
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
#SBATCH --gres=gpu:1
#SBATCH --mem=32G
#SBATCH --time=6:00:00
#SBATCH --job-name=TinyHAR_ms
#SBATCH --output=${PULSE_ROOT}/results/pub_multiseed_exp1_%j.log

# TinyHAR multi-seed scene recognition (5 seeds for best configs)
set -e
PYTHON=python
PROJECT=${PULSE_ROOT}
cd $PROJECT
OUT=$PROJECT/results/published_baselines/exp1_tinyhar_multiseed
mkdir -p $OUT

echo "=== TinyHAR Multi-Seed Scene Recognition ==="

for SEED in 42 123 456 789 2024; do
    for MOD in imu "emg,imu"; do
        for FUSION in early late; do
            # Skip emg,imu+early with non-42 seeds if already done
            echo "--- seed=$SEED / ${MOD} / ${FUSION} ---"
            $PYTHON experiments/train_exp1.py \
                --model tinyhar --modalities $MOD --fusion $FUSION \
                --hidden_dim 32 --epochs 100 --batch_size 16 \
                --lr 1e-3 --weight_decay 1e-3 --downsample 5 \
                --seed $SEED --output_dir $OUT \
                --tag "s${SEED}" 2>&1 | tail -3
        done
    done
done

echo "=== Done ==="