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3cd1076 | 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 | #!/bin/bash
#SBATCH -J posterior # Job name
#SBATCH -o watch_folder/%x_%j.out # log file (out & err)
#SBATCH -N 1 # Total number of nodes requested
#SBATCH --get-user-env # retrieve the users login environment
#SBATCH --mem=64000 # server memory requested (per node)
#SBATCH -t 960:00:00 # Time limit (hh:mm:ss)
#SBATCH --partition=anonymous # Request partition
#SBATCH --constraint="[a5000|a6000|3090]"
#SBATCH --ntasks-per-node=1
#SBATCH --gres=gpu:1 # Type/number of GPUs needed
#SBATCH --open-mode=append # Do not overwrite logs
#SBATCH --requeue # Requeue upon preemption
export HYDRA_FULL_ERROR=1
finetune_path=/path/to/duo.ckpt
srun python -u -m main \
mode=train \
loader.batch_size=2 \
loader.eval_batch_size=2 \
data=openwebtext-split \
model=small \
algo=distillation \
training.finetune_path=$finetune_path \
sampling.num_sample_batches=10 \
sampling.steps=32 \
eval.compute_generative_perplexity=True \
algo.T=512 \
lr_scheduler.num_warmup_steps=500 \
trainer.val_check_interval=1000 \
trainer.max_steps=50000 \
loader.global_batch_size=128 \
training.ema=0.999 \
algo.update_teacher_every=10000 \
optim.lr=6e-5 \
trainer.limit_val_batches=8 \
algo.teacher_ema=False \
algo.linear_growth_dt=false \
+wandb.offline=true
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