Entity relation extraction, a fundamental and essential task in natural language processing (NLP), has garnered significant attention over an extended period., aiming to extract the core of semantic knowledge from unstructured text, i.e., entities and the relations between them. At present, the ...
We use PyTorch (Paszke et al., 2019) to implement our models, and train all models for 1000 rounds with 1 local training epoch per round on each dataset. The batch size for CIFAR-10 and CIFAR-100 is set as 64, and 12 for ISIC. We use the crop-and-flip as the weak data ...
Batch size 20 Initial learning rate 0.001 Max epoch 200 Learning rate drop 20 Drop rate 0.98 First gated graph reasoning 2 Second gated graph reasoning 2 Embedding dropout 0.2 GGNNs dropout 0.4 5.3. Evaluation metric Following the previous works, we employ the score of F1 and Ign F1 as our...
python example/train_bag_cnn.py \ --metric auc \ --dataset nyt10m \ --batch_size 160 \ --lr 0.1 \ --weight_decay 1e-5 \ --max_epoch 100 \ --max_length 128 \ --seed 42 \ --encoder pcnn \ --aggr att Or use the following script to train a BERT model on the Wiki80 dat...
We train our model with a batch size of 16 on 8 GPUs using the SGD optimizer for 9 epochs. The learning rate starts at 0.02 and decays by a factor of 10 at the 7-th epoch. We use ResNet-50 as our back- bone network, which is is pre-trained on...
python example/train_bag_cnn.py \ --metric auc \ --dataset nyt10m \ --batch_size 160 \ --lr 0.1 \ --weight_decay 1e-5 \ --max_epoch 100 \ --max_length 128 \ --seed 42 \ --encoder pcnn \ --aggr att Or use the following script to train a BERT model on the Wiki80 dat...
= [8000,19]21returnDataLoader(ds, arg.BATCH_SIZE, shuffle=True) 在此函数内部第2行我们的数据进行了向量化: 1defpos(x):2'''3map the relative distance between [0, 123)4e1,e2离得过远返回0或者1225默认距离如果超过60返回极端值表示这里的单词与e1关系不大6'''7ifx < -60:8return09if60 >= ...
python main.py --log_name test --cuda 0 --epoch 100 --weight_decay 0.00001 --label_weights 5 --optimizer SGD --lr 0.1 --bio_embed_dim 25 --dep_embed_dim 50 --num_steps 50 --rnn_dropout 0.6 --gcn_dropout 0.6 --train True --batch_size 30 ...
Full size table Methods In this work, we see relation extraction as a classification problem. Specifically, when a sentence and two entity mentions are given, we have to tell if the sentence expresses a specific relation between the two entities. Here we employ the BERT model to solve the re...
Batch size 4 4 4 24 16 16 Gradient accumulation steps 1 2 2 6 1 1 # Epoch 8 8 8 20 10 30 lr for encoder 5e-5 3e-5 1e-5 3e-5 5e-5 2e-5 lr for classifier 1e-4 1e-4 1e-4 3e-5 5e-5 2e-5 γ for margin shifting 0.05 0.05 0.05 0.01 0 0.01Results...