p-doom/crowd-code-dataset-0.2 huggingface dataset:
[tab] scripts_horeka/modelsize_scaling/tokenizer/train_tokenizer_227M.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=8
#SBATCH --ntasks-per-node=4
#SBATCH --time=36:00:00
#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_mihir/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/%x_%j.log
#SBATCH --job-name=train_tokenizer_model_size_scaling_227M

# Log the sbatch script
cat $0

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

tf_records_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft_tfrecord

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/checkpoints/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

ODFSDIR=/mnt/odfs/$SLURM_JOB_ID/stripe_default/checkpoints/
mkdir -p $ODFSDIR

env | grep SLURM

srun python train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --tmp_ckpt_dir $ODFSDIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=3e-5 \
    --log_image_interval=500 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=tokenizer-modelsize-227M-$slurm_job_id \
    --tags tokenizer model-size-scaling L2 227M \
    --entity instant-uv \
    --project jafar \
    --data_dir $tf_records_dir \
    --model_dim=1024 \
    --num_blocks=12 \
    --num_heads=16 \
    --latent_dim=128 \
    --num_latents=2048