File size: 2,303 Bytes
bc7101b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | #!/usr/bin/env bash
# MATH dataset experiment. Resumes from GRPO ckpt, fine-tunes on MATH, runs
# capacity_diagnostic + TF + AR ablations on the final ckpt, pushes to HF.
set -uo pipefail
REPO="LauraGG/blt-reasoner-pilot1"
OUT="/home/ubuntu/work/blt_math"
CFG="/home/ubuntu/experiments/blt_reasoner/configs/exp7b_math.json"
RESUME_FROM="/home/ubuntu/work/blt_grpo_opt13/final"
LOG="/home/ubuntu/work/queue_math.log"
log() { echo "[$(date +%T)] $*" | tee -a "$LOG"; }
mkdir -p "$OUT"
cd /home/ubuntu
export TOKENIZERS_PARALLELISM=false TRANSFORMERS_NO_ADVISORY_WARNINGS=1 HF_HUB_DISABLE_PROGRESS_BARS=1
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
log "==========================================="
log "MATH fine-tune from $RESUME_FROM (GSM8K-trained baseline)"
log "==========================================="
python3 -u -m experiments.blt_reasoner.train --config "$CFG" \
--resume_from "$RESUME_FROM" \
> "$OUT/train.log" 2>&1
log "train exit=$?"
log "Capacity diagnostic on math final"
python3 -u -m experiments.blt_reasoner.scripts.capacity_diagnostic \
--ckpt "$OUT/final" --config "$CFG" --n 100 --K 16 --max_new_tokens 192 \
--out "$OUT/final/capacity_diagnostic.json" \
> "$OUT/capacity.log" 2>&1
log "capacity diag exit=$?"
log "TF ablation (MATH-aware)"
python3 -u -m experiments.blt_reasoner.scripts.ablate_teacher_forced \
--ckpt "$OUT/final" --config "$CFG" --n 200 --K 16 \
--out "$OUT/final/ablation_teacher_forced.json" \
> "$OUT/tf_eval.log" 2>&1
log "TF ablate exit=$?"
log "AR ablation (MATH boxed-answer parsing)"
python3 -u -m experiments.blt_reasoner.eval \
--ckpt "$OUT/final" --config "$CFG" --n 200 --K 16 \
--max_new_tokens 256 --temperature 0.0 \
--out "$OUT/final/ablation_n200_K16.json" \
> "$OUT/ar_eval.log" 2>&1
log "AR ablate exit=$?"
log "pushing math_exp/ to HF"
python3 - <<PYEND
import os
from huggingface_hub import HfApi
token = os.environ.get("BLT_HF_TOKEN", "").strip()
assert token.startswith("hf_"), "BLT_HF_TOKEN missing"
api = HfApi(token=token)
api.upload_folder(folder_path="$OUT", path_in_repo="math_exp",
repo_id="$REPO", repo_type="model",
commit_message="MATH dataset fine-tune from GRPO ckpt")
print("[push] done")
PYEND
log "queue_math.sh DONE"
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