torch.nn.CosineSimilarity(dim=None,eps=1e-6) ``` 其中,`dim`参数指定了计算相似度的维度,`eps`参数是一个小的常数,用于防止除数为零。默认情况下,`dim`参数为None,表示在所有维度上进行相似度计算。 在使用cosinesimilarityloss时,通常需要将模型输出和目标值作为输入,并指定损失函数的类型为cosinesimilaritylo...
2 changes: 1 addition & 1 deletion 2 sentence_transformers/losses/CosineSimilarityLoss.py @@ -8,7 +8,7 @@ class CosineSimilarityLoss(nn.Module): def __init__(self, model: SentenceTransformer, loss_fct=nn.MSELoss(), cos_score_transformation=nn.Identity()): """ CosineSimilarityLoss exp...
Non-Probabilistic Cosine Similarity Loss for Few-Shot Image Classification.Joonhyuk KimInug YoonGyeong-Moon ParkJong-Hwan KimThe British Machine Vision Association and Society for Pattern RecognitionBritish Machine Vision Conference
更重要的是,在大规模的实例级检索任务中,我们的方法实现了新的SOTA,超过了迄今为止在GLDv2上获得的最佳结果,ROxf和RParis分别上涨0.6%、9.1%和17.1%。 3 . OrthoHash: One Loss for All: 在3.1节中,我们从余弦相似度的角度重新表述了深度哈希问题,即解释了余弦相似度中的汉明距离检索和量化误差。在3.2节中,...
Vectorizing the sentence in an N-dimensional space, cosine similarity gives us a (-1,1) measure of the similarity which directly derives from the inner product of the vectors. For sample code, I have used Glove embedding. Average of the word embedding of the sentence have been used. Our ...