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| from sentence_transformers import LoggingHandler, SentenceTransformer, evaluation | |
| from sentence_transformers.readers import InputExample | |
| import csv | |
| import logging | |
| #### Just some code to print debug information to stdout | |
| logging.basicConfig(format='%(asctime)s - %(message)s', | |
| datefmt='%Y-%m-%d %H:%M:%S', | |
| level=logging.INFO, | |
| handlers=[LoggingHandler()]) | |
| logger = logging.getLogger(__name__) | |
| #### /print debug information to stdout | |
| model_name = 'sentence-transformers/paraphrase-albert-base-v2' | |
| #model_name='output/training_OnlineConstrativeLoss-2023-03-11_23-47-34' | |
| #model_name= 'output/training_OnlineConstrativeLoss-2023-03-14_01-24-44' | |
| #86% so far | |
| # model_name = 'output/training_OnlineConstrativeLoss-2023-03-17_16-10-39' | |
| model_sbert = SentenceTransformer(model_name) | |
| dev_sentences1 = [] | |
| dev_sentences2 = [] | |
| dev_labels = [] | |
| with open( "dev_set_training.csv", encoding='utf8') as fIn: | |
| reader = csv.DictReader(fIn, delimiter='|', quoting=csv.QUOTE_NONE) | |
| for row in reader: | |
| dev_sentences1.append(row['ADDRESS1']) | |
| dev_sentences2.append(row['ADDRESS2']) | |
| dev_labels.append(int(row['ARE_SAME'])) | |
| binary_acc_evaluator = evaluation.BinaryClassificationEvaluator(dev_sentences1, dev_sentences2, dev_labels) | |
| binary_acc_evaluator(model_sbert) | |
| print(binary_acc_evaluator) | |