generated_from_trainer

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bert-base-uncased-Twitter_Sentiment_Analysis_v2

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Accuracy Weighted f1 Micro f1 Macro f1 Weighted recall Micro recall Macro recall Weighted precision Micro precision Macro precision
0.3896 1.0 183 0.3073 0.8022 0.7743 0.8022 0.6960 0.8022 0.8022 0.6914 0.8053 0.8022 0.7880
0.2488 2.0 366 0.2937 0.8474 0.8409 0.8474 0.7880 0.8474 0.8474 0.7747 0.8429 0.8474 0.8132
0.1766 3.0 549 0.3115 0.8398 0.8298 0.8398 0.7750 0.8398 0.8398 0.7613 0.8355 0.8398 0.8111
0.1253 4.0 732 0.3354 0.8487 0.8406 0.8487 0.7843 0.8487 0.8487 0.7695 0.8448 0.8487 0.8167
0.09 5.0 915 0.4137 0.8474 0.8447 0.8474 0.7930 0.8474 0.8474 0.7932 0.8455 0.8474 0.7985
0.0677 6.0 1098 0.4872 0.8494 0.8491 0.8494 0.7977 0.8494 0.8494 0.8068 0.8511 0.8494 0.7930
0.0501 7.0 1281 0.4959 0.8576 0.8556 0.8576 0.8066 0.8576 0.8576 0.8063 0.8558 0.8576 0.8105
0.0415 8.0 1464 0.5412 0.8515 0.8505 0.8515 0.8003 0.8515 0.8515 0.8017 0.8503 0.8515 0.8000
0.0323 9.0 1647 0.5969 0.8480 0.8480 0.8480 0.7939 0.8480 0.8480 0.7918 0.8481 0.8480 0.7961
0.0253 10.0 1830 0.5560 0.8549 0.8526 0.8549 0.8024 0.8549 0.8549 0.8016 0.8527 0.8549 0.8073
0.0204 11.0 2013 0.5697 0.8522 0.8494 0.8522 0.7970 0.8522 0.8522 0.7840 0.8482 0.8522 0.8122
0.019 12.0 2196 0.5809 0.8522 0.8507 0.8522 0.8007 0.8522 0.8522 0.8006 0.8503 0.8522 0.8025

Framework versions