p-doom/crowd-code-dataset-0.2 huggingface dataset:
[tab] experiments/train_tokenizer_lr_1e-4_larger_ffn.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=2
#SBATCH --ntasks-per-node=4
#SBATCH --time=24:00:00
#SBATCH --partition=accelerated
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:4
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_franz/big-runs/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_franz/big-runs/%x_%j.log
#SBATCH --job-name=train_tokenizer_lr_sweep_1e-4_larger_ffn

# Log the sbatch script
cat $0

module unload mpi/openmpi/5.0
module unload devel/cuda/12.4
source .venv/bin/activate

array_records_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_new/open_ai_minecraft_arrayrecords_chunked

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=$PWD/checkpoints/$job_name
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

srun python train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --restore_ckpt \
    --save_ckpt \
    --batch_size=96 \
    --ffn_dim=2048 \
    --num_blocks=4 \
    --init_lr=0 \
    --max_lr=1e-4 \
    --log_image_interval=1000 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=mixed-precision-tokenizer-lr-1e-4-larger-ffn \
    --tags tokenizer mixed-precision 1e-4 mixed-precision flash-attention larger-ffn \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir