t5-pegasus pytorch

最新更新

模型效果对比

数据集:LCSTS_new 训练集取前一万条,验证集取前一千条

model bleu rouge-1 rouge-2 rouge-l
t5-pegasus-base 0.1276 0.3490 0.2123 0.3155
t5-copy 0.0938 0.3369 0.1955 0.3086
Pegasus-238M-Chinese 0.1200 0.3252 0.1957 0.2924
Pegasus-523M-Chinese 0.1233 0.3313 0.2032 0.2996
cpt-large 0.1366 0.3550 0.2242 0.3220
prophet-zh 0.1240 0.3419 0.2109 0.3107

数据格式

样例数据

huggingface模型

model_type model_type
t5-pegasus imxly/t5-pegasus
t5copy imxly/t5-copy
Pegasus IDEA-CCNL/Randeng-Pegasus-238M-Chinese
Pegasus IDEA-CCNL/Randeng-Pegasus-523M-Chinese
cpt fnlp/cpt-large
prophet imxly/prophetnet-zh

训练命令

requirements

环境可以参考这个issue

torch >=1.10.0
transformers
pytorch_lightning==1.4.9
torchmetrics==0.5.0

model_type见上方表格

python train.py \
--train_file train.json \
--dev_file dev.json \
--batch_size 6 \
--max_epochs 10 \
--max_source_length 512 \
--max_target_length 300 \
--model_path  imxly/t5-pegasus \
--gpus 4 \
--lr 5e-5 \
--model_type t5-pegasus

参考

https://github.com/ZhuiyiTechnology/t5-pegasus
https://github.com/fastnlp/CPT
https://github.com/IDEA-CCNL/Fengshenbang-LM
https://github.com/microsoft/ProphetNet