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#!/bin/bash
RANK=0
WORLD_SIZE=1
DATA_PATH=<Specify path and file prefix>_text_sentence
CHECKPOINT_PATH=<Specify path>
python pretrain_bert.py \
--num_layers 24 \
--hidden_size 1024 \
--num_attention_heads 16 \
--micro_batch_size 4 \
--global_batch_size 8 \
--seq_length 512 \
--max_position_embeddings 512 \
--train_iters 2000000 \
--lr_decay_iters 990000 \
--save $CHECKPOINT_PATH \
--load $CHECKPOINT_PATH \
--data_path $DATA_PATH \
--vocab_file bert-vocab.txt \
--data_impl mmap \
--split 949,50,1 \
--lr 0.0001 \
--min_lr 0.00001 \
--lr_decay_style linear \
--lr_warmup_fraction .01 \
--weight_decay 1e-2 \
--clip_grad 1.0 \
--log_interval 100 \
--save_interval 10000 \
--eval_interval 1000 \
--eval_iters 10 \
--fp16
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