tner-xlm-roberta-base-all-english / test_panx_dataset-en_span.json
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{"valid": {"f1": 89.29884032114185, "recall": 88.65037194473963, "precision": 89.95686556434221, "summary": " precision recall f1-score support\n\n entity 0.90 0.89 0.89 14115\n\n micro avg 0.90 0.89 0.89 14115\n macro avg 0.90 0.89 0.89 14115\nweighted avg 0.90 0.89 0.89 14115\n"}, "test": {"f1": 89.26135539108982, "recall": 88.54181661148696, "precision": 89.9926847110461, "summary": " precision recall f1-score support\n\n entity 0.90 0.89 0.89 13894\n\n micro avg 0.90 0.89 0.89 13894\n macro avg 0.90 0.89 0.89 13894\nweighted avg 0.90 0.89 0.89 13894\n"}}