              precision    recall  f1-score   support

    negative   0.733238  0.778788  0.755327       660
     neutral   0.757962  0.779963  0.768805      1068
    positive   0.722793  0.728778  0.725773       483
        skip   0.660714  0.501355  0.570108       369
      speech   0.767857  0.868687  0.815166        99

    accuracy                       0.735349      2679
   macro avg   0.728513  0.731514  0.727036      2679
weighted avg   0.732501  0.735349  0.732071      2679


Avg macro Precision 0.7297744200895245
Avg macro Recall 0.7248163039465004
Avg macro F1 0.7229310729744304
Avg weighted F1 0.7281243075011377
{}
transformers pytorch roberta text-classification doi:10.57967/hf/0103 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #doi-10.57967/hf/0103 #autotrain_compatible #endpoints_compatible #region-us 

              precision    recall  f1-score   support

    negative   0.733238  0.778788  0.755327       660
     neutral   0.757962  0.779963  0.768805      1068
    positive   0.722793  0.728778  0.725773       483
        skip   0.660714  0.501355  0.570108       369
      speech   0.767857  0.868687  0.815166        99

    accuracy                       0.735349      2679
   macro avg   0.728513  0.731514  0.727036      2679
weighted avg   0.732501  0.735349  0.732071      2679


Avg macro Precision 0.7297744200895245
Avg macro Recall 0.7248163039465004
Avg macro F1 0.7229310729744304
Avg weighted F1 0.7281243075011377
TAGS
#transformers #pytorch #roberta #text-classification #doi-10.57967/hf/0103 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #roberta #text-classification #doi-10.57967/hf/0103 #autotrain_compatible #endpoints_compatible #region-us 
