roberta-ncc-1shard-rolvb / train-128.sh
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Saving weights and logs of step 2500
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python run_mlm_flax.py \
--output_dir="./" \
--model_type="roberta" \
--config_name="roberta-base" \
--tokenizer_name="NbAiLab/nb-roberta-base" \
--train_file="../train.json" \
--validation_file="../validation.json" \
--max_seq_length="128" \
--weight_decay="0.01" \
--per_device_train_batch_size="128" \
--per_device_eval_batch_size="128" \
--learning_rate="3e-4" \
--warmup_steps="1000" \
--overwrite_output_dir \
--num_train_epochs="18" \
--adam_beta1="0.9" \
--adam_beta2="0.98" \
--logging_steps="500" \
--save_steps="2500" \
--eval_steps="2500" \
--push_to_hub