| export MODEL_DIR=`pwd` | |
| export WANDB_ENTITY="wandb" | |
| export WANDB_PROJECT="hf-flax-gpt2-indonesian" | |
| export WANDB_LOG_MODEL="true" | |
| ./run_clm_flax.py \ | |
| --output_dir="${MODEL_DIR}" \ | |
| --model_type="gpt2" \ | |
| --config_name="${MODEL_DIR}" \ | |
| --tokenizer_name="${MODEL_DIR}" \ | |
| --dataset_name="oscar" \ | |
| --dataset_config_name="unshuffled_deduplicated_id" \ | |
| --do_train --do_eval \ | |
| --block_size="512" \ | |
| --per_device_train_batch_size="24" \ | |
| --per_device_eval_batch_size="24" \ | |
| --learning_rate="0.0024" --warmup_steps="1000" \ | |
| --adam_beta1="0.9" --adam_beta2="0.98" --weight_decay="0.01" \ | |
| --overwrite_output_dir \ | |
| --num_train_epochs="20" \ | |
| --dataloader_num_workers="64" \ | |
| --preprocessing_num_workers="64" \ | |
| --save_steps="10" \ | |
| --eval_steps="10" \ | |
| --max_train_samples="10000" \ | |
| --max_eval_samples="1000" \ | |
| --push_to_hub | |