Web• Expertise in ensemble different CNN architectures and hyper-tuning different parameters like losses (Dice Loss and focal Loss) for better accuracy. Localization of classes using Heatmap, Featmap, and Logitmaps. • Extensive knowledge of data cleaning, Image Processing filters, thresholding, and data augmentation techniques. WebDice Loss for Data-imbalanced NLP Tasks. ACL2024 Xiaofei Sun, Xiaoya Li, Yuxian Meng, Junjun Liang, Fei Wu and Jiwei Li. Coreference Resolution as Query-based Span Prediction. ACL2024 Wei Wu, Fei Wang, Arianna …
Anyone seen work related to data imbalance in NLP?
WebNov 29, 2024 · A problem with dice is that it can have high variance. Getting a single pixel wrong in a tiny object can have the same effect as missing nearly a whole large object, thus the loss becomes highly dependent on the current batch. I don't know details about the generalized dice, but I assume it helps fighting this problem. WebAug 23, 2024 · 14. Adding smooth to the loss does not make it differentiable. What makes it differentiable is. Relaxing the threshold on the prediction: You do not cast y_pred to np.bool, but leave it as a continuous value between 0 and 1. You do not use set operations as np.logical_and, but rather use the element-wise product to approximate the non ... running macro in excel
Segment Anything (CV的GPT-3时刻)_m0_61899108的博客 …
Web你好,我们在复现命名实体识别数据集zh_onto4结果时,按照readme的指导,运行的是scripts/ner_zhonto4/bert_dice.sh. 脚本 ... Web通过定义Dice Loss,替代cross entropy (CE)处理数据不平衡问题。. 原文中的方法适用于很多不同类型数据集的分类任务,这里用诸多经典NLP任务作为BaseLine进行试验,并印 … Web# implementation of dice loss for NLP tasks. import torch: import torch. nn as nn: import torch. nn. functional as F: from torch import Tensor: from typing import Optional: class DiceLoss (nn. Module): """ Dice coefficient for short, is an F1-oriented statistic used to gauge the similarity of two sets. running macro crashes excel