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Make NPROC_PER_NODE customizable in run1000.sh and speedrun.sh
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@ -72,7 +72,7 @@ python -m scripts.tok_eval
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# 5) That's it, everything else (e.g. the learning rates) is adjusted automatically by the training script.
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# Number of processes/GPUs to use
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NPROC_PER_NODE=8
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NPROC_PER_NODE=${NPROC_PER_NODE:-8}
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.base_train -- --depth=32 --device_batch_size=8 --run=$WANDB_RUN
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.base_loss
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@ -83,7 +83,7 @@ echo "Waiting for dataset download to complete..."
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wait $DATASET_DOWNLOAD_PID
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# Number of processes/GPUs to use
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NPROC_PER_NODE=8
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NPROC_PER_NODE=${NPROC_PER_NODE:-8}
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# pretrain the d20 model
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.base_train -- --depth=20 --run=$WANDB_RUN
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