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#!/bin/bash
WORLD_SIZE=8
DISTRIBUTED_ARGS="--nproc_per_node $WORLD_SIZE \
--nnodes 1 \
--node_rank 0 \
--master_addr localhost \
--master_port 6000"
TRAIN_DATA="data/glue_data/MNLI/train.tsv"
VALID_DATA="data/glue_data/MNLI/dev_matched.tsv \
data/glue_data/MNLI/dev_mismatched.tsv"
PRETRAINED_CHECKPOINT=checkpoints/bert_345m
VOCAB_FILE=bert-vocab.txt
CHECKPOINT_PATH=checkpoints/bert_345m_mnli
python -m torch.distributed.launch $DISTRIBUTED_ARGS ./tasks/main.py \
--task MNLI \
--seed 1234 \
--train_data $TRAIN_DATA \
--valid_data $VALID_DATA \
--tokenizer_type BertWordPieceLowerCase \
--vocab_file $VOCAB_FILE \
--epochs 5 \
--pretrained_checkpoint $PRETRAINED_CHECKPOINT \
--tensor_model_parallel_size 1 \
--num_layers 24 \
--hidden_size 1024 \
--num_attention_heads 16 \
--micro_batch_size 8 \
--activations_checkpoint_method uniform \
--lr 5.0e-5 \
--lr_decay_style linear \
--lr_warmup_fraction 0.065 \
--seq_length 512 \
--max_position_embeddings 512 \
--save_interval 500000 \
--save $CHECKPOINT_PATH \
--log_interval 10 \
--eval_interval 100 \
--eval_iters 50 \
--weight_decay 1.0e-1 \
--fp16
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