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python -m sdlm.run_glue \ | |
--model_name_or_path roberta-base \ | |
--dataset_name stsb \ | |
--output_dir tmp \ | |
--do_train \ | |
--do_eval \ | |
--max_seq_length 128 \ | |
--per_device_train_batch_size 32 \ | |
--per_device_eval_batch_size 32 \ | |
--evaluation_strategy epoch \ | |
--save_strategy steps \ | |
--report_to tensorboard \ | |
--overwrite_output_dir \ | |
--pad_to_max_length \ | |
--simplex_value 5 \ | |
--max_train_samples 100 \ | |
--num_train_epochs 3 \ | |
--num_diffusion_steps 5000 \ | |
--num_inference_diffusion_steps 500 \ | |
--conditional_generation seq2seq \ | |
--learning_rate 3e-5 \ | |
--gradient_accumulation_steps 1 \ | |
--lr_scheduler_type cosine \ | |
--beta_schedule squaredcos_improved_ddpm \ | |
--top_p 0.99 \ | |
--warmup_ratio 0.03 \ | |
--logging_steps 50 \ | |
--save_total_limit 1 \ | |
--max_eval_samples 50 \ | |
--skip_special_tokens False # required to cut tokens at the right spot | |