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config.json ADDED
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+ {
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+ "_name_or_path": "bert-large-cased",
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+ "BertForSequenceClassification"
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eval_results.txt ADDED
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+ accuracy = 0.7911111111111111
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+ cls_report = precision recall f1-score support
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+ 0.0 0.7991 0.7991 0.7991 468
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+ accuracy 0.7911 900
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+ macro avg 0.7908 0.7908 0.7908 900
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+ weighted avg 0.7911 0.7911 0.7911 900
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+ eval_loss = 0.4936396519343058
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+ fn = 94
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+ fp = 94
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+ tp = 338
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+ weighted_f1 = 0.7911111111111111
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+ weighted_r = 0.7907763532763533
model_args.json ADDED
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test_eval.txt ADDED
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+ Default classification report:
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+ precision recall f1-score support
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+
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+ F 0.8509 0.8560 0.8534 500
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+ T 0.8551 0.8500 0.8526 500
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+ accuracy 0.8530 1000
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+ weighted avg 0.8530 0.8530 0.8530 1000
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+ Accuracy = 0.8680555555555556
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+ Weighted Recall = 0.8680555555555556
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+ Macro Recall = 0.8680340557275542
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+ Macro Precision = 0.867536231884058
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+ Macro F1 = 0.8677430270218012
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+ ADV
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+ Accuracy = 0.7333333333333333
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+ Weighted Recall = 0.7333333333333333
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+ Weighted Precision = 0.7333333333333333
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+ Weighted F1 = 0.7333333333333333
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+ Macro Recall = 0.7222222222222222
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+ NOUN
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+ Accuracy = 0.8541666666666666
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+ Weighted Recall = 0.8541666666666666
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+ Weighted Precision = 0.8544012331495099
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+ Weighted F1 = 0.8541337014671534
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+ Macro Recall = 0.8541143554056962
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+ Macro Precision = 0.8544347426470589
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+ Macro F1 = 0.8541242828387209
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+ VERB
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+ Accuracy = 0.8557046979865772
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+ Weighted Recall = 0.8557046979865772
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+ Weighted Precision = 0.8561056998556997
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+ Weighted F1 = 0.8556640646999853
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+ Macro Recall = 0.8557046979865772
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+ Macro Precision = 0.8561056998556998
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+ Macro F1 = 0.8556640646999853
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vocab.txt ADDED
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