| ## Phase 1.3 β Fully-trained model ablation (independent truth) | |
| set -e | |
| cd "$(dirname "$0")/.." | |
| PY="conda run -n blackboxnlp --no-capture-output python" | |
| OUT="phase1_ablation" | |
| COMMON="--N 512 --d_model 256 --num_heads 1 \ | |
| --p_train 0.99 --lr 1e-3 --weight_decay 1e-5 --batch_size 128 \ | |
| --num_steps 50000 --save_interval 1000 \ | |
| --early_save_interval 200 --early_save_steps 1000 \ | |
| --print_interval 1000 --use_rms \ | |
| --independent_truth" | |
| # ββ 1. Train: 1 layer Γ 5 seeds ββ | |
| for seed in 0 1 2 3 4; do | |
| out="$OUT/L1_seed${seed}" | |
| echo "" | |
| echo "===== Training L=1 ablated seed=${seed} -> ${out} =====" | |
| $PY train_model.py $COMMON --num_layers 1 --seed $seed --output_path "$out" | |
| done | |
| # ββ 2. Train: 3 layers Γ 5 seeds ββ | |
| for seed in 0 1 2 3 4; do | |
| out="$OUT/L3_seed${seed}" | |
| echo "" | |
| echo "===== Training L=3 ablated seed=${seed} -> ${out} =====" | |
| $PY train_model.py $COMMON --num_layers 3 --seed $seed --output_path "$out" | |
| done | |
| # ββ 3. Analyze each run ββ | |
| for layers in 1 3; do | |
| for seed in 0 1 2 3 4; do | |
| ckpt="$OUT/L${layers}_seed${seed}/checkpoints/ckpt_step50000.pt" | |
| echo "" | |
| echo "===== Analyzing L=${layers} ablated seed=${seed} =====" | |
| $PY analyze_model.py --checkpoint "$ckpt" --all | |
| done | |
| done | |
| echo "" | |
| echo "===== ALL DONE =====" | |