liuluyeah/Pytorch-Multi-Task-Multi-class-Classification liuluyeah/Pytorch_exs liuluyeah/mt-dnn liuluyeah/keras-mmoe MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning(https://upos-sz-mirrorkodo.bilivideo.com/upgcxcode/98/31/175913198/175913198-1-208.mp4?e...
二分类(Binary classification) 标签是两个类别之一,例如是或否 根据某人的健康情况预测某人是否患有心脏病。 多类分类(Multi-class classification) 标签是多个类别(大于两个)中的一个 确定照片是食物、人还是狗。 多标签分类(Multi-label classification) 标签是多个类别(大于两个)中的一个或是多个,不固定 预测维...
gate_input = DNN(gate_dnn_hidden_units, dnn_activation, l2_reg_dnn, dnn_dropout, dnn_use_bn, seed=2022, name='gate_'+task_names[i])(dnn_input) gate_out = Dense(num_experts, use_bias=False, activation='softmax', name='gate_softmax_'+task_names[i])(gate_input) gate_out = La...
I am working on Multiclass Classification (4 classes) for Language Task and I am using the BERT model for classification task. I am following this blog post Transfer Learning for NLP: Fine-Tuning BERT for Text Classification. My BERT Fine Tuned model returns nn.LogSoftmax(dim=1)...
F1Score(task="multiclass", num_classes=num_classes), Precision(task="multiclass",num_classes=num_classes), Recall(task="multiclass",num_classes=num_classes), CohenKappa(task="multiclass",num_classes=num_classes) ] maximize_list=[True,True,True,True,True] ...
For binary classification tasks, the labels should be 0 or 1. For multi-class classification tasks, the labels should be integers from 0 to num_classes-1. 定义优化器和损失函数: optimizer = torch.optim.Adam(classifier.parameters(), lr=1e-5) # Adjust learning rate and optimizer as per ...
三、 Classification 分类 四、快速搭建网络 五、网络的保存和提取 六、批数据训练(mini_batch training) day 04 一、优化器Optimizer加速神经网络训练(深度学习) 二、Opttimizer优化器 三、 卷积神经网络(CNN) 四、什么是LSTM循环卷积网络(RNN) 五、自编码/非监督学习(Autoencoder) ...
Binary vs Multi-class vs Multi-label Classification. Image by Author One of the key reasons why I wanted to do this project is to familiarize myself with theWeights and Biases (W&B)library that has been a hot buzz all over my tech Twitter, along with theHuggingF...
In this article, you’ll be introduced to multi-task learning, the art of creating a Deep Learning model that can do more than one task.
使用pytorch实现了TextCNN,TextRNN,FastText,TextRCNN,BiLSTM_Attention,DPCNN,Transformer。github:Chinese-Text-Classification-Pytorch,开箱即用。 二、中文数据集: 我从THUCNews中抽取了20万条新闻标题,文本长度在20到30之间。一共10个类别,每类2万条。