前言：
眼前我们对“步进程序算法”大概比较看重，姐妹们都需要分析一些“步进程序算法”的相关资讯。那么小编也在网上网罗了一些有关“步进程序算法””的相关内容，希望看官们能喜欢，各位老铁们快快来了解一下吧！Requirements
torch==1.2.0transformers==2.5.1fairseq==0.9.0
It needs at least 4 GPUs on your device if you want to finetune GPT2-Large baseline, otherwise 2 GPUs are enough.
Download Data
python download/download_cnn.pypython download/download_writing_prompts.pyTrain
python train.py \ --dataset [cnn/wp] \ --prog_steps null-{...}-full \ --first_model [bart/gpt2/gpt2-large]--first_model specifies the type of the first-stage model.The training log will be stored in training_logs/{your setting}/:
training_logs/{setting}/log.txt: evaluation loss of each checkpoint.training_logs/{setting}/ckpt_gens/step{}.txt: ~10 generation examples on dev set of each checkpoint.training_logs/{setting}/best_model.pt: best checkpoint model according to evaluation loss.
Check scripts/train_all.sh for all commands for training.
Generate
python generate.py \ --dataset [cnn/wp] \ --prog_steps null-{...}-full \ --first_model [bart/gpt2/gpt2-large]Generated texts will be stored in generated_texts/{your setting}/:
generated_texts/{setting}/gen.txt: generation log.generated_texts/{setting}/gen.pickle: all generated texts stored into a pickle file.
Check scripts/gen_all.sh for all commands for generation.
Evaluate
python evaluate.py \ --dataset [cnn/wp] \ --prog_steps null-{...}-full \ --first_model [bart/gpt2/gpt2-large]Check scripts/eval_all.sh for all commands for evaluation.
Present Results
python present_eval_results.py \ --dataset [cnn/wp] \ --metric [ms_jaccard/frechet_bert_distance/tfidf_distance/forward_backward_bleu]
Github
【论文】
标签： #步进程序算法
