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#!/usr/bin/env bash\n#SBATCH --nodes=1\n#SBATCH --ntasks-per-node=1\n#SBATCH --time=5:00:00\n#SBATCH --partition=accelerated\n#SBATCH --cpus-per-task=8\n#SBATCH --gres=gpu:1\n#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_alfred/logs_training_tokenizer/%x_%j.log\n#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_alfred/logs_training_tokenizer/%x_%j.log\n#SBATCH --job-name=train_tokenizer_overfit_sample_size_2_mio\n\n# Log the sbatch script\ncat $0\n\nmodule unload mpi/openmpi/5.0\nmodule unload devel/cuda/12.4\nsource .venv_jafar/bin/activate\n\nws_dir='/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/'\ntf_records_dir=$ws_dir/data/knoms_tfrecords_200_shards\n\njob_name=$SLURM_JOB_NAME\nslurm_job_id=$SLURM_JOB_ID\n\ntags=("overfit_sample", "tokenizer", "model_scaling", "alfred")\n\nCHECKPOINT_DIR=$ws_dir/checkpoints/$job_name_$slurm_job_id\nmkdir -p $CHECKPOINT_DIR\n\nenv | grep SLURM\n\nsrun python train_tokenizer_single_sample.py \\n --ckpt_dir $CHECKPOINT_DIR \\n --batch_size=1 \\n --min_lr=4.3e-5 \\n --max_lr=4.3e-4 \\n --log_image_interval=10 \\n --log \\n --entity instant-uv \\n --project jafar \\n --name $job_name \\n --tags $tags \\n --model_dim 128 \\n --data_dir $tf_records_dir\n\n
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