Update training evaluation

indiquo/training/candidate/TrainCandidateClassifierST.py

@@ -31,9 +31,9 @@ def train(train_folder_path, output_folder_path, model_name):
     train_dataloader = DataLoader(train_examples, shuffle=True, batch_size=16)
     train_loss = losses.ContrastiveLoss(model=model)
 
-    evaluator = evaluation.BinaryClassificationEvaluator(val_sentences_1, val_sentences_2, val_labels, write_csv=False)
+    evaluator = evaluation.BinaryClassificationEvaluator(val_sentences_1, val_sentences_2, val_labels)
 
     num_epochs = 5
     warmup_steps = math.ceil(len(train_dataloader) * num_epochs * 0.1)  # 10% of train data for warm-up
     model.fit(train_objectives=[(train_dataloader, train_loss)], epochs=num_epochs, warmup_steps=warmup_steps,
-              evaluator=evaluator, evaluation_steps=1000, output_path=output_folder_path)
+              evaluator=evaluator, output_path=output_folder_path)