您尚未登录账户请先登录您的atyun账户，方可使用该功能
您的企业账号申请正在审核中审核通过后即可使用此功能，请耐心等待~
数据集:
allenai/multinews_sparse_mean
任务:
摘要生成
语言:
en
计算机处理:
monolingual大小:
10K<n<100K语言创建人:
expert-generated批注创建人:
expert-generated源数据集:
original许可:
other
中文This is a copy of the Multi-News dataset, except the input source documents of its test split have been replaced by a sparse retriever. The retrieval pipeline used:
- query : The summary field of each example
- corpus : The union of all documents in the train , validation and test splits
- retriever : BM25 via PyTerrier with default settings
- top-k strategy : "mean" , i.e. the number of documents retrieved, k , is set as the mean number of documents seen across examples in this dataset, in this case k==3
Retrieval results on the train set:
| Recall@100 | Rprec | Precision@k | Recall@k |
|---|---|---|---|
| 0.8793 | 0.7460 | 0.6403 | 0.7417 |
Retrieval results on the validation set:
| Recall@100 | Rprec | Precision@k | Recall@k |
|---|---|---|---|
| 0.8748 | 0.7453 | 0.6361 | 0.7442 |
Retrieval results on the test set:
| Recall@100 | Rprec | Precision@k | Recall@k |
|---|---|---|---|
| 0.8775 | 0.7480 | 0.6370 | 0.7443 |