            precision    recall  f1-score   support

    negative   0.681957  0.675758  0.678843       660
     neutral   0.707845  0.735019  0.721176      1068
    positive   0.596591  0.652174  0.623145       483
        skip   0.583062  0.485095  0.529586       369
      speech   0.827160  0.676768  0.744444        99

    accuracy                       0.668906      2679
    macro avg  0.679323  0.644963  0.659439      2679
    w avg      0.668631  0.668906  0.667543      2679


3 Runs:
Avg macro Precision 0.6747772329026972
Avg macro Recall 0.6436866944877477
Avg macro F1 0.654867154097531
Avg weighted F1 0.6649503767906553
{}
transformers pytorch bert text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

            precision    recall  f1-score   support

    negative   0.681957  0.675758  0.678843       660
     neutral   0.707845  0.735019  0.721176      1068
    positive   0.596591  0.652174  0.623145       483
        skip   0.583062  0.485095  0.529586       369
      speech   0.827160  0.676768  0.744444        99

    accuracy                       0.668906      2679
    macro avg  0.679323  0.644963  0.659439      2679
    w avg      0.668631  0.668906  0.667543      2679


3 Runs:
Avg macro Precision 0.6747772329026972
Avg macro Recall 0.6436866944877477
Avg macro F1 0.654867154097531
Avg weighted F1 0.6649503767906553
TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
