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python3 -m albert.run_pretraining \
--input_file=${STORAGE_BUCKET}/indicnlp-datasets/multilingual/orig/small_tfrecords/*\
--output_dir=${STORAGE_BUCKET}/albert-base-orig \
--albert_config_file=configs/albert_base_config.json \
--do_train \
--train_batch_size=4096 \
--max_seq_length=128 \
--max_predictions_per_seq=20 \
--optimizer='lamb' \
--learning_rate=.00176 \
--num_train_steps=125000 \
--num_warmup_steps=3125 \
--save_checkpoints_steps=5000 \
--use_tpu \
--tpu_name=node-2 \
--tpu_zone=europe-west4-a \
--num_tpu_cores=8
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