[core/auto] task_type = core/auto/supervised_task cache_dir = ./cache # model [core/model/mass] pretrained_name = mass-base-uncased num_beams = 5 no_repeat_ngram_size = 0 max_gen_seq_length = 15 repetition_penalty = 1.0 # dataset [core/dataset] # data columns: id, num, query, doc, label, score data_name = fuliucansheng/data_for_test [core/dataset/train] preprocess_funcs = ['core/process/mass_for_generation(query, doc)'] [core/dataset/dev] preprocess_funcs = ['core/process/mass_for_tokens(query)', 'core/process/mass_for_next_tokens(doc)'] [core/dataset/test] preprocess_funcs = ['core/process/mass_for_tokens(query)'] # process [core/process/mass] pretrained_name = mass-base-uncased max_seq_length = 24 max_gen_seq_length = 15 # task [core/auto/supervised_task] model = core/model/mass_for_generation optim = core/optim/adam dataset = core/dataset/auto loss_fn = core/loss/lm score_fn = core/score/bleu monitor_fns = ['core/score/bleu', 'core/score/rouge1', 'core/score/rouge2', 'core/score/rougel'] output_header = query,doc post_process_fn = partial(core/process/mass_for_decode) opt_fp16 = O1 from_ckpt_dir = ${core/auto:cache_dir} to_ckpt_dir = ${core/auto:cache_dir} output_path = ${core/auto:cache_dir}/output.txt train_batch_size = 128 dev_batch_size = 128 test_batch_size = 256