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Saving weights and logs at step 500
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#!/usr/bin/env bash
#export TOKENIZERS_PARALLELISM=0
python ./run_mlm_flax.py \
--push_to_hub \
--output_dir="./" \
--model_type="big_bird" \
--config_name="./" \
--tokenizer_name="./" \
--max_seq_length="4096" \
--weight_decay="0.0095" \
--warmup_steps="5000" \
--overwrite_output_dir \
--adam_beta1="0.9" \
--adam_beta2="0.98" \
--logging_steps="250" \
--eval_steps="500" \
--num_train_epochs="5" \
--preprocessing_num_workers="96" \
--save_steps="500" \
--learning_rate="5e-5" \
--per_device_train_batch_size="2" \
--per_device_eval_batch_size="2" \
--save_total_limit="5"\
--max_eval_samples="500"\
--overwrite_cache False \
--gradient_accumulation_steps="4" \
#--resume_from_checkpoint="./"\
#--adafactor \
#--dtype="bfloat16" \