gbure

Graph-based approaches on unsupervised relation extraction evaluated as a fewshot problem
git clone https://esimon.eu/repos/gbure.git
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soares_fewrel.py (576B)


      1 from gbure.model.fewshot import Model
      2 from torch.optim import SGD as Optimizer
      3 
      4 
      5 dataset_name = "FewRel"
      6 shot = 1
      7 way = 5
      8 linguistic_similarity = "dot"
      9 
     10 # From Table 1
     11 transformer_model = "bert-base-cased"
     12 post_transformer_layer = "layer_norm"
     13 max_epoch = 10
     14 learning_rate = 1e-4
     15 accumulated_batch_size = 256
     16 
     17 # Guessed
     18 validation_metric = "accuracy"
     19 early_stopping_patience = 2
     20 latent_metric_scale = "standard"
     21 latent_dot_mean = 1067.65
     22 latent_dot_std = 111.17
     23 clip_gradient = 1
     24 
     25 # Implementation details
     26 seed = 0
     27 amp = True
     28 initial_grad_scale = 1
     29 batch_size = 2
     30 workers = 8