run_adftd_ablation.sh

#!/bin/bash
# Claims 3 & 4: ADFTD ablation (Scratch / Pre-trained L_rec / Pre-trained L_rec+L_div)
# and the Ti-MAE / SimMTM fine-tuning-promotion comparison of Table 4.
set -u
cd /home/avesha/ritesh/paper-repro
PY=.venvr/bin/python
DATA=data/ADFTD/processed
OUT=results/adftd
mkdir -p $OUT
SEEDS="41 42 43"
COMMON="--data-dir $DATA --batch-size 256 --pre-epochs 100 --ft-epochs 100 --patience 10 --seeds $SEEDS"

run () { # name, extra args
  local name=$1; shift
  if [ -s "$OUT/$name.json" ]; then echo "skip $name"; return; fi
  echo "=== $name ==="
  $PY tsfp/train.py $COMMON "$@" --out "$OUT/$name.json" 2>&1 | tail -4
}

run tsfp_scratch      --model tsfp   --mode scratch
run tsfp_rec          --model tsfp   --mode pretrain_ft --use-div 0
run tsfp_rec_div      --model tsfp   --mode pretrain_ft --use-div 1
run timae_scratch     --model timae  --mode scratch
run timae_pretrain    --model timae  --mode pretrain_ft
run simmtm_scratch    --model simmtm --mode scratch
run simmtm_pretrain   --model simmtm --mode pretrain_ft
echo "ALL DONE"