bert uncased keyword extractor This model is a fine tuned version of bert base uncased on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.1247 Precision: 0.8547 Recall: 0.8825 Accuracy: 0.9741 F1: 0.8684 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: learning rate: 2e 05 train batch size: 16 eval batch size: 16 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear num epochs: 8 mixed precision training: Native AMP Training results Training Loss Epoch Step Validation Loss Precision Recall Accuracy F1 : : : : : : : : : : : : : : : : 0.165 1.0 1875 0.1202 0.7109 0.7766 0.9505 0.7423 0.1211 2.0 3750 0.1011 0.7801 0.8186 0.9621 0.7989 0.0847 3.0 5625 0.0945 0.8292 0.8044 0.9667 0.8166 0.0614 4.0 7500 0.0927 0.8409 0.8524 0.9711 0.8466 0.0442 5.0 9375 0.1057 0.8330 0.8738 0.9712 0.8529 0.0325 6.0 11250 0.1103 0.8585 0.8743 0.9738 0.8663 0.0253 7.0 13125 0.1204 0.8453 0.8825 0.9735 0.8635 0.0203 8.0 15000 0.1247 0.854…
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