--- library_name: transformers tags: [] --- ``` ================================================================================ ASPEKT | ACC | F1-MACRO | WYNIK ================================================================================ overall_experience | 0.8406 | 0.7705 | (Neg/None/Pos) location | 0.9468 | 0.8534 | (Neg/None/Pos) cleanliness | 0.9548 | 0.9243 | (Neg/None/Pos) bed_comfort | 0.8925 | 0.8122 | (Neg/None/Pos) size_space | 0.8034 | 0.7348 | (Neg/None/Pos) kitchen | 0.8914 | 0.8038 | (Neg/None/Pos) wifi | 0.9888 | 0.8632 | (Neg/None/Pos) noise | 0.9588 | 0.9216 | (Neg/None/Pos) safety | 0.9018 | 0.6855 | (Neg/None/Pos) host_contact | 0.9553 | 0.9265 | (Neg/None/Pos) value_for_money | 0.9350 | 0.7852 | (Neg/None/Pos) food | 0.8778 | 0.6203 | (Neg/None/Pos) -------------------------------------------------------------------------------- >>> SZCZEGÓŁY DLA overall_experience precision recall f1-score support Negatywny 0.89 0.86 0.87 423 Brak/OK 0.39 0.83 0.53 403 Pozytywny 0.99 0.84 0.91 2913 accuracy 0.84 3739 macro avg 0.75 0.84 0.77 3739 weighted avg 0.91 0.84 0.86 3739 >>> SZCZEGÓŁY DLA location precision recall f1-score support Negatywny 0.49 0.96 0.65 92 Brak/OK 0.96 0.92 0.94 1301 Pozytywny 0.97 0.96 0.97 2346 accuracy 0.95 3739 macro avg 0.81 0.95 0.85 3739 weighted avg 0.96 0.95 0.95 3739 >>> SZCZEGÓŁY DLA cleanliness precision recall f1-score support Negatywny 0.79 0.92 0.85 302 Brak/OK 0.98 0.96 0.97 2392 Pozytywny 0.96 0.95 0.96 1045 accuracy 0.95 3739 macro avg 0.91 0.94 0.92 3739 weighted avg 0.96 0.95 0.96 3739 >>> SZCZEGÓŁY DLA bed_comfort precision recall f1-score support Negatywny 0.63 0.95 0.76 171 Brak/OK 0.99 0.88 0.93 3102 Pozytywny 0.61 0.95 0.74 466 accuracy 0.89 3739 macro avg 0.74 0.93 0.81 3739 weighted avg 0.93 0.89 0.90 3739 >>> SZCZEGÓŁY DLA size_space precision recall f1-score support Negatywny 0.54 0.94 0.68 258 Brak/OK 0.94 0.80 0.86 2801 Pozytywny 0.58 0.76 0.66 680 accuracy 0.80 3739 macro avg 0.68 0.83 0.73 3739 weighted avg 0.85 0.80 0.81 3739 >>> SZCZEGÓŁY DLA kitchen precision recall f1-score support Negatywny 0.61 0.96 0.74 164 Brak/OK 0.99 0.88 0.93 3109 Pozytywny 0.61 0.92 0.73 466 accuracy 0.89 3739 macro avg 0.74 0.92 0.80 3739 weighted avg 0.93 0.89 0.90 3739 >>> SZCZEGÓŁY DLA wifi precision recall f1-score support Negatywny 0.86 0.98 0.92 55 Brak/OK 1.00 0.99 0.99 3648 Pozytywny 0.53 0.94 0.68 36 accuracy 0.99 3739 macro avg 0.80 0.97 0.86 3739 weighted avg 0.99 0.99 0.99 3739 >>> SZCZEGÓŁY DLA noise precision recall f1-score support Negatywny 0.81 0.92 0.86 305 Brak/OK 0.99 0.97 0.98 2881 Pozytywny 0.92 0.94 0.93 553 accuracy 0.96 3739 macro avg 0.90 0.94 0.92 3739 weighted avg 0.96 0.96 0.96 3739 >>> SZCZEGÓŁY DLA safety precision recall f1-score support Negatywny 0.45 0.92 0.60 111 Brak/OK 0.99 0.90 0.95 3490 Pozytywny 0.36 0.88 0.51 138 accuracy 0.90 3739 macro avg 0.60 0.90 0.69 3739 weighted avg 0.95 0.90 0.92 3739 >>> SZCZEGÓŁY DLA host_contact precision recall f1-score support Negatywny 0.77 0.97 0.86 203 Brak/OK 0.97 0.93 0.95 1568 Pozytywny 0.97 0.97 0.97 1968 accuracy 0.96 3739 macro avg 0.90 0.96 0.93 3739 weighted avg 0.96 0.96 0.96 3739 >>> SZCZEGÓŁY DLA value_for_money precision recall f1-score support Negatywny 0.43 0.92 0.59 106 Brak/OK 0.99 0.94 0.96 3357 Pozytywny 0.76 0.86 0.81 276 accuracy 0.94 3739 macro avg 0.73 0.90 0.79 3739 weighted avg 0.95 0.94 0.94 3739 >>> SZCZEGÓŁY DLA food precision recall f1-score support Negatywny 0.21 0.95 0.35 19 Brak/OK 0.99 0.87 0.93 3424 Pozytywny 0.42 0.93 0.58 296 accuracy 0.88 3739 macro avg 0.54 0.92 0.62 3739 weighted avg 0.94 0.88 0.90 3739 ``` ## Model Details ### Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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