| # | |
| # Finetunes the ESM-1b Transformer model on supervised data. | |
| # | |
| #SBATCH --cluster=<clustername> | |
| #SBATCH --partition=<partitionname> | |
| #SBATCH --account=<accountname> | |
| #SBATCH --job-name=esm_finetune | |
| #SBATCH --gres=gpu:1 # Number of GPU(s) per node. | |
| #SBATCH --cpus-per-task=2 # CPU cores/threads | |
| #SBATCH --mem=32000M # memory per node | |
| #SBATCH --time=0-24:00 # Max time (DD-HH:MM) | |
| #SBATCH --ntasks=1 # Only set to >1 if you want to use multi-threading | |
| export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK | |
| dataset=$1 | |
| runid=$2 | |
| epochs=$3 | |
| n_train=$4 | |
| seed=$5 | |
| model_name="esm1b" | |
| init_model="/mnt/esm_weights/${model_name}.pt" | |
| kwargs=$6 | |
| python src/esm_finetune.py data_esm/${dataset}/data.csv \ | |
| data_esm/${dataset}/wt.fasta \ | |
| /mnt/inference/${dataset}/esm_finetune/${runid} \ | |
| --epochs $epochs --n_train $n_train --toks_per_batch 512 \ | |
| --model_location $init_model --seed $seed \ | |
| $kwargs | |