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nerui-lora-r16-3

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metadata
language:
  - id
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: nerui-lora-r16-3
    results: []

nerui-lora-r16-3

This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0440
  • Location Precision: 0.8925
  • Location Recall: 0.9651
  • Location F1: 0.9274
  • Location Number: 86
  • Organization Precision: 0.9375
  • Organization Recall: 0.9270
  • Organization F1: 0.9322
  • Organization Number: 178
  • Person Precision: 0.9764
  • Person Recall: 0.9688
  • Person F1: 0.9725
  • Person Number: 128
  • Overall Precision: 0.9394
  • Overall Recall: 0.9490
  • Overall F1: 0.9442
  • Overall Accuracy: 0.9879

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100.0

Training results

Training Loss Epoch Step Validation Loss Location Precision Location Recall Location F1 Location Number Organization Precision Organization Recall Organization F1 Organization Number Person Precision Person Recall Person F1 Person Number Overall Precision Overall Recall Overall F1 Overall Accuracy
1.0702 1.0 96 0.6541 0.0 0.0 0.0 86 0.0 0.0 0.0 178 0.0 0.0 0.0 128 0.0 0.0 0.0 0.8435
0.6334 2.0 192 0.5098 0.0 0.0 0.0 86 0.6 0.0169 0.0328 178 0.0 0.0 0.0 128 0.375 0.0077 0.015 0.8440
0.5002 3.0 288 0.3652 0.25 0.0233 0.0426 86 0.3671 0.1629 0.2257 178 0.3252 0.3125 0.3187 128 0.3381 0.1811 0.2359 0.8758
0.3547 4.0 384 0.2533 0.4889 0.2558 0.3359 86 0.5178 0.5730 0.544 178 0.5776 0.7266 0.6436 128 0.5385 0.5536 0.5459 0.9247
0.2464 5.0 480 0.1831 0.7013 0.6279 0.6626 86 0.6136 0.7584 0.6784 178 0.7655 0.8672 0.8132 128 0.6787 0.7653 0.7194 0.9503
0.1901 6.0 576 0.1432 0.7553 0.8256 0.7889 86 0.7353 0.8427 0.7853 178 0.8897 0.9453 0.9167 128 0.7880 0.8724 0.8281 0.9636
0.159 7.0 672 0.1220 0.7684 0.8488 0.8066 86 0.7853 0.8427 0.8130 178 0.8849 0.9609 0.9213 128 0.8141 0.8827 0.8470 0.9671
0.1398 8.0 768 0.0960 0.7895 0.8721 0.8287 86 0.8289 0.8708 0.8493 178 0.9462 0.9609 0.9535 128 0.8568 0.9005 0.8781 0.9738
0.1294 9.0 864 0.0884 0.8295 0.8488 0.8391 86 0.8272 0.8876 0.8564 178 0.9470 0.9766 0.9615 128 0.8662 0.9082 0.8867 0.9752
0.1202 10.0 960 0.0821 0.8152 0.8721 0.8427 86 0.8325 0.9213 0.8747 178 0.9328 0.9766 0.9542 128 0.8605 0.9286 0.8933 0.9768
0.1081 11.0 1056 0.0783 0.8172 0.8837 0.8492 86 0.8715 0.8764 0.8739 178 0.9466 0.9688 0.9575 128 0.8834 0.9082 0.8956 0.9776
0.1022 12.0 1152 0.0719 0.8370 0.8953 0.8652 86 0.8617 0.9101 0.8852 178 0.9398 0.9766 0.9579 128 0.8814 0.9286 0.9043 0.9781
0.0991 13.0 1248 0.0685 0.8667 0.9070 0.8864 86 0.8846 0.9045 0.8944 178 0.9542 0.9766 0.9653 128 0.9032 0.9286 0.9157 0.9803
0.0916 14.0 1344 0.0666 0.8043 0.8605 0.8315 86 0.8876 0.8876 0.8876 178 0.9538 0.9688 0.9612 128 0.89 0.9082 0.8990 0.9781
0.088 15.0 1440 0.0613 0.8556 0.8953 0.875 86 0.8871 0.9270 0.9066 178 0.9612 0.9688 0.9650 128 0.9037 0.9337 0.9184 0.9811
0.0851 16.0 1536 0.0614 0.8404 0.9186 0.8778 86 0.8804 0.9101 0.8950 178 0.9612 0.9688 0.9650 128 0.8968 0.9311 0.9136 0.9814
0.0821 17.0 1632 0.0598 0.8462 0.8953 0.8701 86 0.8846 0.9045 0.8944 178 0.9688 0.9688 0.9688 128 0.9027 0.9235 0.9130 0.9811
0.0791 18.0 1728 0.0573 0.8764 0.9070 0.8914 86 0.8852 0.9101 0.8975 178 0.9612 0.9688 0.9650 128 0.9077 0.9286 0.9180 0.9816
0.0792 19.0 1824 0.0576 0.8478 0.9070 0.8764 86 0.8907 0.9157 0.9030 178 0.9612 0.9688 0.9650 128 0.9035 0.9311 0.9171 0.9806
0.0734 20.0 1920 0.0563 0.8211 0.9070 0.8619 86 0.8846 0.9045 0.8944 178 0.9843 0.9766 0.9804 128 0.9010 0.9286 0.9146 0.9814
0.0716 21.0 2016 0.0563 0.8316 0.9186 0.8729 86 0.8876 0.8876 0.8876 178 0.9612 0.9688 0.9650 128 0.8980 0.9209 0.9093 0.9816
0.0703 22.0 2112 0.0565 0.8602 0.9302 0.8939 86 0.8717 0.9157 0.8932 178 0.9843 0.9766 0.9804 128 0.9042 0.9388 0.9212 0.9819
0.0687 23.0 2208 0.0558 0.7843 0.9302 0.8511 86 0.8844 0.8596 0.8718 178 0.9766 0.9766 0.9766 128 0.8883 0.9133 0.9006 0.9800
0.0669 24.0 2304 0.0564 0.7980 0.9186 0.8541 86 0.8902 0.8652 0.8775 178 0.9688 0.9688 0.9688 128 0.8925 0.9107 0.9015 0.9811
0.0653 25.0 2400 0.0542 0.8163 0.9302 0.8696 86 0.9075 0.8820 0.8946 178 0.9766 0.9766 0.9766 128 0.9073 0.9235 0.9153 0.9825
0.0638 26.0 2496 0.0524 0.8061 0.9186 0.8587 86 0.9153 0.9101 0.9127 178 0.9843 0.9766 0.9804 128 0.9104 0.9337 0.9219 0.9825
0.0618 27.0 2592 0.0521 0.8511 0.9302 0.8889 86 0.9157 0.9157 0.9157 178 0.9766 0.9766 0.9766 128 0.92 0.9388 0.9293 0.9841
0.0611 28.0 2688 0.0531 0.8 0.9302 0.8602 86 0.9133 0.8876 0.9003 178 0.9843 0.9766 0.9804 128 0.9075 0.9260 0.9167 0.9822
0.06 29.0 2784 0.0506 0.8511 0.9302 0.8889 86 0.9011 0.9213 0.9111 178 0.9843 0.9766 0.9804 128 0.9156 0.9413 0.9283 0.9825
0.0586 30.0 2880 0.0494 0.8696 0.9302 0.8989 86 0.9050 0.9101 0.9076 178 0.9843 0.9766 0.9804 128 0.9221 0.9362 0.9291 0.9838
0.0549 31.0 2976 0.0497 0.8602 0.9302 0.8939 86 0.9056 0.9157 0.9106 178 0.9843 0.9766 0.9804 128 0.92 0.9388 0.9293 0.9838
0.0549 32.0 3072 0.0481 0.8889 0.9302 0.9091 86 0.9061 0.9213 0.9136 178 0.9764 0.9688 0.9725 128 0.9246 0.9388 0.9316 0.9854
0.0561 33.0 3168 0.0483 0.8182 0.9419 0.8757 86 0.9075 0.8820 0.8946 178 0.9764 0.9688 0.9725 128 0.9073 0.9235 0.9153 0.9827
0.0566 34.0 3264 0.0455 0.8977 0.9186 0.9080 86 0.9286 0.9494 0.9389 178 0.9764 0.9688 0.9725 128 0.9370 0.9490 0.9430 0.9870
0.0529 35.0 3360 0.0477 0.8889 0.9302 0.9091 86 0.8913 0.9213 0.9061 178 0.9764 0.9688 0.9725 128 0.9177 0.9388 0.9281 0.9852
0.0507 36.0 3456 0.0481 0.8617 0.9419 0.9000 86 0.9071 0.9326 0.9197 178 0.9764 0.9688 0.9725 128 0.9183 0.9464 0.9322 0.9854
0.0536 37.0 3552 0.0457 0.8681 0.9186 0.8927 86 0.9050 0.9101 0.9076 178 0.9764 0.9688 0.9725 128 0.9194 0.9311 0.9252 0.9852
0.0512 38.0 3648 0.0491 0.8438 0.9419 0.8901 86 0.9006 0.9157 0.9081 178 0.9843 0.9766 0.9804 128 0.9134 0.9413 0.9271 0.9841
0.0489 39.0 3744 0.0478 0.8646 0.9651 0.9121 86 0.9171 0.9326 0.9248 178 0.9843 0.9766 0.9804 128 0.9257 0.9541 0.9397 0.9862
0.0503 40.0 3840 0.0456 0.8791 0.9302 0.9040 86 0.9162 0.9213 0.9188 178 0.9843 0.9766 0.9804 128 0.9295 0.9413 0.9354 0.9862
0.0502 41.0 3936 0.0473 0.8438 0.9419 0.8901 86 0.9310 0.9101 0.9205 178 0.9843 0.9766 0.9804 128 0.9270 0.9388 0.9328 0.9860
0.0478 42.0 4032 0.0452 0.8791 0.9302 0.9040 86 0.9111 0.9213 0.9162 178 0.9843 0.9766 0.9804 128 0.9271 0.9413 0.9342 0.9870
0.0456 43.0 4128 0.0476 0.8333 0.9302 0.8791 86 0.9218 0.9270 0.9244 178 0.9843 0.9766 0.9804 128 0.9204 0.9439 0.9320 0.9849
0.0457 44.0 4224 0.0481 0.8617 0.9419 0.9000 86 0.9266 0.9213 0.9239 178 0.9764 0.9688 0.9725 128 0.9271 0.9413 0.9342 0.9852
0.0462 45.0 4320 0.0481 0.8710 0.9419 0.9050 86 0.9257 0.9101 0.9178 178 0.9764 0.9688 0.9725 128 0.9291 0.9362 0.9327 0.9849
0.045 46.0 4416 0.0502 0.8351 0.9419 0.8852 86 0.9133 0.8876 0.9003 178 0.9764 0.9688 0.9725 128 0.9144 0.9260 0.9202 0.9838
0.0453 47.0 4512 0.0465 0.8696 0.9302 0.8989 86 0.9222 0.9326 0.9274 178 0.9764 0.9688 0.9725 128 0.9273 0.9439 0.9355 0.9857
0.0439 48.0 4608 0.0463 0.8710 0.9419 0.9050 86 0.9261 0.9157 0.9209 178 0.9764 0.9688 0.9725 128 0.9293 0.9388 0.9340 0.9857
0.0431 49.0 4704 0.0462 0.8710 0.9419 0.9050 86 0.9153 0.9101 0.9127 178 0.9764 0.9688 0.9725 128 0.9244 0.9362 0.9303 0.9854
0.041 50.0 4800 0.0463 0.8617 0.9419 0.9000 86 0.9371 0.9213 0.9292 178 0.9764 0.9688 0.9725 128 0.9318 0.9413 0.9365 0.9860
0.0412 51.0 4896 0.0459 0.8696 0.9302 0.8989 86 0.9322 0.9270 0.9296 178 0.9764 0.9688 0.9725 128 0.9318 0.9413 0.9365 0.9857
0.0408 52.0 4992 0.0464 0.8710 0.9419 0.9050 86 0.9266 0.9213 0.9239 178 0.9764 0.9688 0.9725 128 0.9295 0.9413 0.9354 0.9852
0.0412 53.0 5088 0.0482 0.8723 0.9535 0.9111 86 0.9379 0.9326 0.9352 178 0.9764 0.9688 0.9725 128 0.9347 0.9490 0.9418 0.9865
0.0411 54.0 5184 0.0444 0.8889 0.9302 0.9091 86 0.9379 0.9326 0.9352 178 0.9764 0.9688 0.9725 128 0.9391 0.9439 0.9415 0.9862
0.042 55.0 5280 0.0456 0.8817 0.9535 0.9162 86 0.9371 0.9213 0.9292 178 0.9764 0.9688 0.9725 128 0.9367 0.9439 0.9403 0.9860
0.0396 56.0 5376 0.0454 0.8617 0.9419 0.9000 86 0.9213 0.9213 0.9213 178 0.9764 0.9688 0.9725 128 0.9248 0.9413 0.9330 0.9868
0.0376 57.0 5472 0.0471 0.8617 0.9419 0.9000 86 0.9318 0.9213 0.9266 178 0.9764 0.9688 0.9725 128 0.9295 0.9413 0.9354 0.9854
0.04 58.0 5568 0.0450 0.8617 0.9419 0.9000 86 0.9209 0.9157 0.9183 178 0.9764 0.9688 0.9725 128 0.9246 0.9388 0.9316 0.9862
0.0385 59.0 5664 0.0450 0.8617 0.9419 0.9000 86 0.9153 0.9101 0.9127 178 0.9764 0.9688 0.9725 128 0.9221 0.9362 0.9291 0.9862
0.0399 60.0 5760 0.0455 0.8526 0.9419 0.8950 86 0.92 0.9045 0.9122 178 0.9764 0.9688 0.9725 128 0.9219 0.9337 0.9278 0.9862
0.0393 61.0 5856 0.0449 0.8804 0.9419 0.9101 86 0.9318 0.9213 0.9266 178 0.9764 0.9688 0.9725 128 0.9342 0.9413 0.9377 0.9870
0.0382 62.0 5952 0.0443 0.8804 0.9419 0.9101 86 0.9322 0.9270 0.9296 178 0.9764 0.9688 0.9725 128 0.9343 0.9439 0.9391 0.9873
0.0382 63.0 6048 0.0442 0.8710 0.9419 0.9050 86 0.9171 0.9326 0.9248 178 0.9764 0.9688 0.9725 128 0.9252 0.9464 0.9357 0.9865
0.038 64.0 6144 0.0434 0.8901 0.9419 0.9153 86 0.9266 0.9213 0.9239 178 0.9764 0.9688 0.9725 128 0.9342 0.9413 0.9377 0.9868
0.0362 65.0 6240 0.0459 0.8602 0.9302 0.8939 86 0.9379 0.9326 0.9352 178 0.9764 0.9688 0.9725 128 0.9320 0.9439 0.9379 0.9860
0.0369 66.0 6336 0.0464 0.8617 0.9419 0.9000 86 0.9253 0.9045 0.9148 178 0.9764 0.9688 0.9725 128 0.9266 0.9337 0.9301 0.9854
0.0361 67.0 6432 0.0450 0.8817 0.9535 0.9162 86 0.9326 0.9326 0.9326 178 0.9764 0.9688 0.9725 128 0.9347 0.9490 0.9418 0.9873
0.0352 68.0 6528 0.0453 0.8710 0.9419 0.9050 86 0.9379 0.9326 0.9352 178 0.9764 0.9688 0.9725 128 0.9345 0.9464 0.9404 0.9865
0.0356 69.0 6624 0.0451 0.8817 0.9535 0.9162 86 0.9322 0.9270 0.9296 178 0.9764 0.9688 0.9725 128 0.9345 0.9464 0.9404 0.9865
0.0337 70.0 6720 0.0442 0.8542 0.9535 0.9011 86 0.9322 0.9270 0.9296 178 0.9764 0.9688 0.9725 128 0.9275 0.9464 0.9369 0.9868
0.0371 71.0 6816 0.0447 0.8723 0.9535 0.9111 86 0.9218 0.9270 0.9244 178 0.9764 0.9688 0.9725 128 0.9275 0.9464 0.9369 0.9865
0.0342 72.0 6912 0.0442 0.9121 0.9651 0.9379 86 0.9371 0.9213 0.9292 178 0.9764 0.9688 0.9725 128 0.9440 0.9464 0.9452 0.9870
0.0355 73.0 7008 0.0440 0.8913 0.9535 0.9213 86 0.9432 0.9326 0.9379 178 0.9764 0.9688 0.9725 128 0.9418 0.9490 0.9454 0.9873
0.0353 74.0 7104 0.0437 0.8737 0.9651 0.9171 86 0.9535 0.9213 0.9371 178 0.9764 0.9688 0.9725 128 0.9416 0.9464 0.9440 0.9868
0.034 75.0 7200 0.0441 0.8830 0.9651 0.9222 86 0.9429 0.9270 0.9348 178 0.9764 0.9688 0.9725 128 0.9394 0.9490 0.9442 0.9873
0.0341 76.0 7296 0.0466 0.8646 0.9651 0.9121 86 0.9270 0.9270 0.9270 178 0.9764 0.9688 0.9725 128 0.9277 0.9490 0.9382 0.9862
0.0345 77.0 7392 0.0454 0.8817 0.9535 0.9162 86 0.9314 0.9157 0.9235 178 0.9764 0.9688 0.9725 128 0.9342 0.9413 0.9377 0.9865
0.0351 78.0 7488 0.0442 0.8925 0.9651 0.9274 86 0.9477 0.9157 0.9314 178 0.9764 0.9688 0.9725 128 0.9439 0.9439 0.9439 0.9868
0.033 79.0 7584 0.0434 0.8817 0.9535 0.9162 86 0.9322 0.9270 0.9296 178 0.9764 0.9688 0.9725 128 0.9345 0.9464 0.9404 0.9870
0.0324 80.0 7680 0.0443 0.8830 0.9651 0.9222 86 0.9270 0.9270 0.9270 178 0.9764 0.9688 0.9725 128 0.9323 0.9490 0.9406 0.9868
0.033 81.0 7776 0.0450 0.8737 0.9651 0.9171 86 0.9432 0.9326 0.9379 178 0.9764 0.9688 0.9725 128 0.9372 0.9515 0.9443 0.9870
0.0334 82.0 7872 0.0447 0.8817 0.9535 0.9162 86 0.9266 0.9213 0.9239 178 0.9764 0.9688 0.9725 128 0.9320 0.9439 0.9379 0.9870
0.0324 83.0 7968 0.0437 0.8913 0.9535 0.9213 86 0.9218 0.9270 0.9244 178 0.9764 0.9688 0.9725 128 0.9322 0.9464 0.9392 0.9876
0.0344 84.0 8064 0.0442 0.8804 0.9419 0.9101 86 0.9368 0.9157 0.9261 178 0.9764 0.9688 0.9725 128 0.9364 0.9388 0.9376 0.9870
0.0333 85.0 8160 0.0445 0.8617 0.9419 0.9000 86 0.9306 0.9045 0.9174 178 0.9764 0.9688 0.9725 128 0.9289 0.9337 0.9313 0.9860
0.0317 86.0 8256 0.0466 0.8710 0.9419 0.9050 86 0.9368 0.9157 0.9261 178 0.9764 0.9688 0.9725 128 0.9340 0.9388 0.9364 0.9860
0.0337 87.0 8352 0.0451 0.8817 0.9535 0.9162 86 0.9314 0.9157 0.9235 178 0.9764 0.9688 0.9725 128 0.9342 0.9413 0.9377 0.9865
0.0339 88.0 8448 0.0444 0.8817 0.9535 0.9162 86 0.9483 0.9270 0.9375 178 0.9764 0.9688 0.9725 128 0.9416 0.9464 0.9440 0.9873
0.0322 89.0 8544 0.0441 0.8817 0.9535 0.9162 86 0.9314 0.9157 0.9235 178 0.9764 0.9688 0.9725 128 0.9342 0.9413 0.9377 0.9865
0.0303 90.0 8640 0.0452 0.8830 0.9651 0.9222 86 0.9425 0.9213 0.9318 178 0.9764 0.9688 0.9725 128 0.9392 0.9464 0.9428 0.9873
0.0309 91.0 8736 0.0448 0.8830 0.9651 0.9222 86 0.9314 0.9157 0.9235 178 0.9764 0.9688 0.9725 128 0.9343 0.9439 0.9391 0.9868
0.0311 92.0 8832 0.0447 0.8817 0.9535 0.9162 86 0.9314 0.9157 0.9235 178 0.9764 0.9688 0.9725 128 0.9342 0.9413 0.9377 0.9865
0.0329 93.0 8928 0.0445 0.8925 0.9651 0.9274 86 0.9429 0.9270 0.9348 178 0.9764 0.9688 0.9725 128 0.9418 0.9490 0.9454 0.9876
0.031 94.0 9024 0.0445 0.8925 0.9651 0.9274 86 0.9429 0.9270 0.9348 178 0.9764 0.9688 0.9725 128 0.9418 0.9490 0.9454 0.9876
0.0323 95.0 9120 0.0441 0.8913 0.9535 0.9213 86 0.9429 0.9270 0.9348 178 0.9764 0.9688 0.9725 128 0.9416 0.9464 0.9440 0.9873
0.0304 96.0 9216 0.0436 0.8913 0.9535 0.9213 86 0.9266 0.9213 0.9239 178 0.9764 0.9688 0.9725 128 0.9343 0.9439 0.9391 0.9876
0.0317 97.0 9312 0.0437 0.8925 0.9651 0.9274 86 0.9375 0.9270 0.9322 178 0.9764 0.9688 0.9725 128 0.9394 0.9490 0.9442 0.9881
0.0308 98.0 9408 0.0437 0.8925 0.9651 0.9274 86 0.9375 0.9270 0.9322 178 0.9764 0.9688 0.9725 128 0.9394 0.9490 0.9442 0.9879
0.0304 99.0 9504 0.0440 0.8925 0.9651 0.9274 86 0.9375 0.9270 0.9322 178 0.9764 0.9688 0.9725 128 0.9394 0.9490 0.9442 0.9879
0.0301 100.0 9600 0.0440 0.8925 0.9651 0.9274 86 0.9375 0.9270 0.9322 178 0.9764 0.9688 0.9725 128 0.9394 0.9490 0.9442 0.9879

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.15.2