python -m torch.distributed.launch --nproc_per_node 8 run_train.py --overwrite_output_dir \ --task_name sum --dataset_name cnndm \ --train_data_path data/cnndm \ --dev_data_path data/cnndm \ --test_data_path data/cnndm \ --load_tokenized_data False \ --generator_num_cand_generated 8 --generator_num_cand_picked 8 \ --num_cand_generated 16 --num_cand_picked 3 --candidate_pick_strategy bottom \ --do_train True --do_eval False --do_predict False --prediction_loss_only False \ --per_device_train_batch_size 2 --per_device_eval_batch_size 4 \ --gradient_accumulation_steps 4 \ --generator_learning_rate 5e-5 --reranker_learning_rate 1e-5 \ --num_train_epochs 3 \ --evaluation_strategy steps --eval_steps 1000 \ --logging_strategy steps --logging_steps 500 \ --save_strategy steps --save_steps 1000 --save_total_limit 20 \ --iteration_steps 1000 --iteration_reranker_steps 500 \ --load_best_model_at_end True \ --metric_for_best_model generator_eval_rouge1 --greater_is_better True \ --reranker_model_name_or_path warmup-ranker/saves/roberta-large-cnndm \ --generator_model_name_or_path warmup-generator/saves/bart-large-cnndm \ --output_dir saves/JGR-large-cnndm \ --generator_max_source_length 1020 --reranker_max_source_length 400 --generator_max_target_length 109 --reranker_max_target_length 109 \ --cache_data \ --disable_tqdm False python -m torch.distributed.launch --nproc_per_node 8 run_train.py --overwrite_output_dir \ --task_name sum --dataset_name samsum \ --train_data_path data/samsum \ --dev_data_path data/samsum \ --test_data_path data/samsum \ --load_tokenized_data False \ --generator_num_cand_generated 8 --generator_num_cand_picked 8 \ --num_cand_generated 16 --num_cand_picked 3 --candidate_pick_strategy bottom \ --do_train True --do_eval False --do_predict False --prediction_loss_only False \ --per_device_train_batch_size 2 --per_device_eval_batch_size 4 \ --gradient_accumulation_steps 4 \ --generator_learning_rate 1e-5 --reranker_learning_rate 5e-6 \ --num_train_epochs 10 \ --evaluation_strategy steps --eval_steps 462 \ --logging_strategy steps --logging_steps 231 \ --save_strategy steps --save_steps 462 --save_total_limit 20 \ --iteration_steps 462 --iteration_reranker_steps 231 \ --load_best_model_at_end True \ --metric_for_best_model generator_eval_rouge1 --greater_is_better True \ --reranker_model_name_or_path warmup-ranker/saves/roberta-large-samsum \ --generator_model_name_or_path warmup-generator/saves/bart-large-samsum \ --output_dir saves/JGR-large-samsum \ --generator_max_source_length 1020 --reranker_max_source_length 400 --generator_max_target_length 109 --reranker_max_target_length 109 \ --cache_data \ --disable_tqdm False python -m torch.distributed.launch --nproc_per_node 8 run_train.py --overwrite_output_dir \ --task_name qg --dataset_name squadqg \ --train_data_path data/squadqg \ --dev_data_path data/squadqg \ --test_data_path data/squadqg \ --load_tokenized_data False \ --generator_num_cand_generated 8 --generator_num_cand_picked 8 \ --num_cand_generated 16 --num_cand_picked 3 --candidate_pick_strategy bottom \ --do_train True --do_eval False --do_predict False --prediction_loss_only False \ --per_device_train_batch_size 2 --per_device_eval_batch_size 4 \ --gradient_accumulation_steps 2 \ --generator_learning_rate 5e-5 --reranker_learning_rate 1e-5 \ --num_train_epochs 3 \ --evaluation_strategy steps --eval_steps 500 \ --logging_strategy steps --logging_steps 500 \ --save_strategy steps --save_steps 250 --save_total_limit 20 \ --iteration_steps 500 --iteration_reranker_steps 250 \ --load_best_model_at_end True \ --metric_for_best_model generator_eval_rougeL --greater_is_better True \ --reranker_model_name_or_path warmup-ranker/saves/roberta-large-squadqg \ --generator_model_name_or_path warmup-generator/saves/bart-large-squadqg \ --output_dir saves/JGR-large-squadqg \ --generator_max_source_length 600 --reranker_max_source_length 435 --generator_max_target_length 65 --reranker_max_target_length 65 \ --cache_data \ --disable_tqdm False python -m torch.distributed.launch --nproc_per_node 8 run_train.py --overwrite_output_dir \ --task_name dialog --dataset_name personachat \ --train_data_path data/personachat \ --dev_data_path data/personachat \ --test_data_path data/personachat \ --load_tokenized_data False \ --generator_num_cand_generated 8 --generator_num_cand_picked 8 \ --num_cand_generated 16 --num_cand_picked 3 --candidate_pick_strategy bottom \ --do_train True --do_eval False --do_predict False --prediction_loss_only False \ --per_device_train_batch_size 2 --per_device_eval_batch_size 4 \ --gradient_accumulation_steps 4 \ --generator_learning_rate 5e-5 --reranker_learning_rate 1e-5 \ --num_train_epochs 3 \ --evaluation_strategy steps --eval_steps 1000 \ --logging_strategy steps --logging_steps 500 \ --save_strategy steps --save_steps 1000 --save_total_limit 20 \ --iteration_steps 1000 --iteration_reranker_steps 500 \ --load_best_model_at_end True \ --metric_for_best_model generator_eval_rouge1 --greater_is_better True \ --reranker_model_name_or_path warmup-ranker/saves/roberta-large-personachat \ --generator_model_name_or_path warmup-generator/saves/bart-large-personachat \ --output_dir saves/JGR-large-personachat \ --generator_max_source_length 550 --reranker_max_source_length 430 --generator_max_target_length 70 --reranker_max_target_length 70 \ --cache_data \ --disable_tqdm False