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#! /bin/bash
# Runs the "217M" parameter biencoder model for ICT retriever
RANK=0
WORLD_SIZE=1
PRETRAINED_BERT_PATH=<Specify path of pretrained BERT model>
TEXT_DATA_PATH=<Specify path and file prefix of the text data>
TITLE_DATA_PATH=<Specify path and file prefix od the titles>
CHECKPOINT_PATH=<Specify path>
python pretrain_ict.py \
--num-layers 12 \
--hidden-size 768 \
--num-attention-heads 12 \
--tensor-model-parallel-size 1 \
--micro-batch-size 32 \
--seq-length 256 \
--max-position-embeddings 512 \
--train-iters 100000 \
--vocab-file bert-vocab.txt \
--tokenizer-type BertWordPieceLowerCase \
--DDP-impl torch \
--bert-load ${PRETRAINED_BERT_PATH} \
--log-interval 100 \
--eval-interval 1000 \
--eval-iters 10 \
--retriever-report-topk-accuracies 1 5 10 20 100 \
--retriever-score-scaling \
--load $CHECKPOINT_PATH \
--save $CHECKPOINT_PATH \
--data-path ${TEXT_DATA_PATH} \
--titles-data-path ${TITLE_DATA_PATH} \
--lr 0.0001 \
--lr-decay-style linear \
--weight-decay 1e-2 \
--clip-grad 1.0 \
--lr-warmup-fraction 0.01 \
--save-interval 4000 \
--exit-interval 8000 \
--query-in-block-prob 0.1 \
--fp16
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