change config

Configuration/config.ini

@@ -4,7 +4,7 @@ transformers = 4.16.2
 [DATASET_PARAMS]
 symbols_vocab_size = 26
 atom_vocab_size = 18
-max_len_sentence = 83
+max_len_sentence = 290
 max_atoms_in_sentence = 900
 max_atoms_in_one_type = 360
 
@@ -24,7 +24,7 @@ sinkhorn_iters = 5
 
 [MODEL_TRAINING]
 batch_size = 32
-pretrain_linker_epochs = 1
-epoch = 1
+pretrain_linker_epochs = 10
+epoch = 20
 seed_val = 42
 learning_rate = 2e-3
\ No newline at end of file

SuperTagger @ ce978e6d

-Subproject commit 4963a6b33a361caf3dd8c458fead6b8352b034cd
+Subproject commit ce978e6d389c6e126d162f86a4b627cda167313c

train.py

@@ -6,7 +6,7 @@ from utils import read_csv_pgbar
 from Configuration import Configuration
 
 torch.cuda.empty_cache()
-nb_sentences = 4*32
+nb_sentences = 10000000
 file_path_axiom_links = 'Datasets/goldANDsilver_dataset_links.csv'
 model_tagger = "models/flaubert_super_98_V2_50e.pt"
 
@@ -28,6 +28,5 @@ print("#" * 20)
 neural_proof_net = NeuralProofNet(model_tagger)
 neural_proof_net.train_neuralproofnet(df_axiom_links, validation_rate=0.1, epochs=epochs, batch_size=batch_size,
                                       checkpoint=True, tensorboard=True)
-neural_proof_net.linker.predict_without_categories("le chat est noir")
 print("#" * 20)
 print("#" * 20)