generated_from_trainer

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codebert-base-finetuned-code-ner-15e

This model is a fine-tuned version of microsoft/codebert-base 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 Precision Recall F1 Accuracy
No log 1.0 191 0.4566 0.5021 0.4220 0.4585 0.8827
No log 2.0 382 0.3756 0.5699 0.5764 0.5731 0.9043
0.5133 3.0 573 0.3605 0.6001 0.5767 0.5882 0.9093
0.5133 4.0 764 0.3500 0.6130 0.6130 0.6130 0.9153
0.5133 5.0 955 0.3501 0.6337 0.6172 0.6254 0.9178
0.2203 6.0 1146 0.3645 0.6250 0.6352 0.6300 0.9163
0.2203 7.0 1337 0.3488 0.6263 0.6422 0.6341 0.9189
0.1457 8.0 1528 0.3575 0.6372 0.6397 0.6384 0.9194
0.1457 9.0 1719 0.3662 0.6406 0.6343 0.6375 0.9189
0.1457 10.0 1910 0.3613 0.6374 0.6473 0.6423 0.9201
0.107 11.0 2101 0.3716 0.6329 0.6544 0.6435 0.9197
0.107 12.0 2292 0.3754 0.6328 0.6487 0.6406 0.9193
0.107 13.0 2483 0.3826 0.6395 0.6490 0.6443 0.9204
0.0863 14.0 2674 0.3821 0.6368 0.6535 0.6451 0.9200
0.0863 15.0 2865 0.3831 0.6363 0.6494 0.6428 0.9197

Evaluation results

Algorithm Application Class Code_Block Data_Structure Data_Type Device Error_Name File_Name File_Type Function HTML_XML_Tag Keyboard_IP Language Library Operating_System Output_Block User_Interface_Element User_Name Value Variable Version Website overall_precision overall_recall overall_f1 overall_accuracy
precision 0 0.619835 0.680851 0.455629 0.813187 0.592593 0.395062 0.181818 0.800505 0.775956 0.757664 0.585366 0.333333 0.689769 0.61807 0.769231 0.0212766 0.542214 0.4375 0.370236 0.560479 0.883721 0.382353 0.626308 0.642171 0.63414 0.918927
recall 0 0.677711 0.696864 0.494253 0.840909 0.8 0.533333 0.333333 0.794486 0.628319 0.631387 0.470588 0.0169492 0.81323 0.546279 0.843373 0.04 0.653846 0.518519 0.52987 0.54482 0.914089 0.270833 0.626308 0.642171 0.63414 0.918927
f1 0 0.647482 0.688765 0.474156 0.826816 0.680851 0.453901 0.235294 0.797484 0.694377 0.688786 0.521739 0.0322581 0.746429 0.579961 0.804598 0.0277778 0.592821 0.474576 0.435897 0.552538 0.898649 0.317073 0.626308 0.642171 0.63414 0.918927
number 31 664 1148 696 264 120 60 30 798 226 822 102 59 257 551 83 25 442 54 385 859 291 48 0.626308 0.642171 0.63414 0.918927

Framework versions