| USE_DDP=false |
|
|
| if [ $USE_DDP = false ]; then |
| |
| CUDA_VISIBLE_DEVICES=1 \ |
| python examples/glen_phase1/train_glen.py \ |
| --output_dir logs/model_glen_marco/GLEN_P1_base \ |
| --model_name_or_path t5-base \ |
| --load_best_model_at_end True \ |
| --query_type gtq_qg20_doc \ |
| --per_device_train_batch_size 128 \ |
| --per_device_eval_batch_size 16 \ |
| --gradient_accumulation_steps 8 \ |
| --dropout_rate 0.1 \ |
| --Rdrop 0.00 \ |
| --aug_query False \ |
| --input_dropout 1 \ |
| --id_class t5_bm25_7 \ |
| --dataset_name marco_passage \ |
| --test100 0 \ |
| --tree 1 \ |
| --pretrain_decoder True \ |
| --max_input_length 156 \ |
| --val_check_interval 0.1 \ |
| --tie_word_embeddings True \ |
| --decoder_input doc_rep \ |
| --max_output_length 9 \ |
| --num_return_sequences 10 \ |
| --logging_steps 100 \ |
| --overwrite_output_dir \ |
| --wandb_tag glen_base \ |
| --do_eval \ |
| --seed 42 |
| else |
| |
| CUDA_VISIBLE_DEVICES=0,1 \ |
| python -m torch.distributed.launch --nproc_per_node=2 examples/glen_phase1/train_glen.py \ |
| --ddp_find_unused_parameters False \ |
| --output_dir logs/model_glen_marco/GLEN_base \ |
| --model_name_or_path t5-base \ |
| --load_best_model_at_end True \ |
| --query_type gtq_qg20_doc \ |
| --per_device_train_batch_size 128 \ |
| --per_device_eval_batch_size 16 \ |
| --gradient_accumulation_steps 8 \ |
| --dropout_rate 0.1 \ |
| --Rdrop 0.00 \ |
| --aug_query False \ |
| --aug_query_type corrupted_query \ |
| --input_dropout 1 \ |
| --id_class t5_bm25_7 \ |
| --dataset_name marco_passage \ |
| --test100 0 \ |
| --tree 1 \ |
| --pretrain_decoder True \ |
| --max_input_length 156 \ |
| --val_check_interval 0.1 \ |
| --tie_word_embeddings True \ |
| --decoder_input doc_rep \ |
| --max_output_length 9 \ |
| --num_return_sequences 10 \ |
| --logging_steps 100 \ |
| --overwrite_output_dir \ |
| --wandb_tag glen_base \ |
| --do_eval \ |
| --seed 42 |
|
|
| fi |
|
|