When summarizing an article, humans are habituated to fuse multiple related sentences to make the summary more concise and coherent. But most of the previous work focuses on the grammaticality of the fusion process and neglects the mechanism behind which sentences should be fused together. And ...
]test_dataset = dataset["test"]# 4. Define a loss functionloss = MultipleNegativesRankingLoss(model)# 5. (Optional) Specify training argumentsargs = SentenceTransformerTrainingArguments(# Required parameter: output_dir="models/mpnet-base-all-nli-triplet",# Optional training parameters: num_t...
CHANGCHUN, May 14 (Xinhua) -- Zhao Weiguo, former board chairman of China's Tsinghua Unigroup, was on Wednesday sentenced to death with a two-year reprieve for multiple crimes. Zhao was convicted of embezzlement, illegal profit-seeking, and breach of trust causing harm to the interests of th...
Simple sentence: A sentence with one independent clause and no dependent clauses. My aunt enjoyed taking the hayride with you. China's Han Dynasty marked an official recognition of Confucianism. Compound Sentence: A sentence wi...
What Is Wrong With ANOVA and Multiple Regression? Analyzing Sentence Reading Times With Hierarchical Linear Models - Richter - 2006Richter, T. (2006), What is wrong with ANOVA and multiple regression? Analyzing sentence reading times with hierarchical linear models, Discourse Processes, 41(3), 221...
Multiple ChoiceChoose the correct answer to complete each sentence.1. My brother and I ___ going to the park.a) isb) amc) ared) be 相关知识点: 试题来源: 解析 c) are 句子主语“My brother and I”是复数,因此需用复数形式的be动词。选项分析如下: - a) is:单数,不适用于复数主语。 - ...
English has a type of verb called aphrasal verb. These are verbs made up of multiple words, and one is usually a preposition. “Cheer up,”“run over,”“log on,” and “leave off” are all examples of phrasal verbs, and often sentences that use phrasal verbs end with a preposition:...
Load several loss functions to train with # (anchor, positive), (anchor, positive, negative) mnrl_loss = MultipleNegativesRankingLoss(model) # (sentence_A, sentence_B) + class softmax_loss = SoftmaxLoss(model) # (sentence_A, sentence_B) + score cosent_loss = CoSENTLoss(model) # ...
fromsentence_transformers.lossesimportCoSENTLoss, MultipleNegativesRankingLoss, SoftmaxLoss # 1. Load a model to finetune model = SentenceTransformer("bert-base-uncased") # 2. Loadseveral Datasets to train with # (anchor, positive) all_nli_pair_train = load_dataset("sentence-transformers/all-nl...
Paper tables with annotated results for A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations