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nerui-pt-pl30-3

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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: nerui-pt-pl30-3
    results: []

nerui-pt-pl30-3

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: 0.0628
  • Location Precision: 0.8830
  • Location Recall: 0.9651
  • Location F1: 0.9222
  • Location Number: 86
  • Organization Precision: 0.9641
  • Organization Recall: 0.9045
  • Organization F1: 0.9333
  • Organization Number: 178
  • Person Precision: 0.9766
  • Person Recall: 0.9766
  • Person F1: 0.9766
  • Person Number: 128
  • Overall Precision: 0.9486
  • Overall Recall: 0.9413
  • Overall F1: 0.9449
  • Overall Accuracy: 0.9870

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
0.8558 1.0 96 0.3807 0.0 0.0 0.0 86 0.2548 0.2247 0.2388 178 0.3008 0.3125 0.3065 128 0.2740 0.2041 0.2339 0.8694
0.36 2.0 192 0.2204 0.376 0.5465 0.4455 86 0.6121 0.5674 0.5889 178 0.6730 0.8359 0.7456 128 0.5679 0.6505 0.6064 0.9374
0.1992 3.0 288 0.1151 0.7711 0.7442 0.7574 86 0.7053 0.7528 0.7283 178 0.9124 0.9766 0.9434 128 0.7878 0.8240 0.8055 0.9638
0.1329 4.0 384 0.0878 0.72 0.8372 0.7742 86 0.7892 0.8202 0.8044 178 0.9185 0.9688 0.9430 128 0.8143 0.8724 0.8424 0.9719
0.1134 5.0 480 0.0738 0.7935 0.8488 0.8202 86 0.8333 0.8708 0.8516 178 0.9545 0.9844 0.9692 128 0.8634 0.9031 0.8828 0.9760
0.0973 6.0 576 0.0726 0.7222 0.9070 0.8041 86 0.8882 0.8034 0.8437 178 0.9766 0.9766 0.9766 128 0.8715 0.8827 0.8771 0.9752
0.0878 7.0 672 0.0579 0.8316 0.9186 0.8729 86 0.8490 0.9157 0.8811 178 0.984 0.9609 0.9723 128 0.8859 0.9311 0.9080 0.9806
0.0801 8.0 768 0.0546 0.8495 0.9186 0.8827 86 0.8586 0.9213 0.8889 178 0.9762 0.9609 0.9685 128 0.8927 0.9337 0.9127 0.9830
0.0753 9.0 864 0.0527 0.8265 0.9419 0.8804 86 0.8983 0.8933 0.8958 178 0.9843 0.9766 0.9804 128 0.9080 0.9311 0.9194 0.9838
0.0674 10.0 960 0.0558 0.8061 0.9186 0.8587 86 0.8659 0.8708 0.8683 178 0.9766 0.9766 0.9766 128 0.8864 0.9158 0.9009 0.9795
0.0613 11.0 1056 0.0607 0.7757 0.9651 0.8601 86 0.9423 0.8258 0.8802 178 0.9843 0.9766 0.9804 128 0.9103 0.9056 0.9079 0.9798
0.0561 12.0 1152 0.0463 0.8462 0.8953 0.8701 86 0.8833 0.8933 0.8883 178 0.9766 0.9766 0.9766 128 0.9048 0.9209 0.9128 0.9841
0.0536 13.0 1248 0.0508 0.8617 0.9419 0.9000 86 0.8811 0.9157 0.8981 178 0.9764 0.9688 0.9725 128 0.9064 0.9388 0.9223 0.9841
0.0507 14.0 1344 0.0509 0.8706 0.8605 0.8655 86 0.9086 0.8933 0.9008 178 0.9766 0.9766 0.9766 128 0.9227 0.9133 0.9179 0.9841
0.0482 15.0 1440 0.0486 0.8696 0.9302 0.8989 86 0.9143 0.8989 0.9065 178 0.9606 0.9531 0.9569 128 0.9188 0.9235 0.9211 0.9841
0.0442 16.0 1536 0.0458 0.8617 0.9419 0.9000 86 0.9375 0.9270 0.9322 178 0.9766 0.9766 0.9766 128 0.9322 0.9464 0.9392 0.9862
0.046 17.0 1632 0.0471 0.8681 0.9186 0.8927 86 0.9298 0.8933 0.9112 178 0.9843 0.9766 0.9804 128 0.9332 0.9260 0.9296 0.9849
0.0403 18.0 1728 0.0576 0.8587 0.9186 0.8876 86 0.9244 0.8933 0.9086 178 0.9843 0.9766 0.9804 128 0.9284 0.9260 0.9272 0.9841
0.0399 19.0 1824 0.0512 0.8791 0.9302 0.9040 86 0.9357 0.8989 0.9169 178 0.9688 0.9688 0.9688 128 0.9333 0.9286 0.9309 0.9860
0.0381 20.0 1920 0.0482 0.8646 0.9651 0.9121 86 0.9529 0.9101 0.9310 178 0.9764 0.9688 0.9725 128 0.9389 0.9413 0.9401 0.9862
0.0339 21.0 2016 0.0447 0.8804 0.9419 0.9101 86 0.9474 0.9101 0.9284 178 0.9535 0.9609 0.9572 128 0.9337 0.9337 0.9337 0.9870
0.035 22.0 2112 0.0519 0.8526 0.9419 0.8950 86 0.8944 0.9045 0.8994 178 0.9764 0.9688 0.9725 128 0.9104 0.9337 0.9219 0.9849
0.032 23.0 2208 0.0497 0.8804 0.9419 0.9101 86 0.9467 0.8989 0.9222 178 0.9843 0.9766 0.9804 128 0.9433 0.9337 0.9385 0.9868
0.0322 24.0 2304 0.0556 0.8526 0.9419 0.8950 86 0.9034 0.8933 0.8983 178 0.9767 0.9844 0.9805 128 0.915 0.9337 0.9242 0.9843
0.0297 25.0 2400 0.0588 0.8542 0.9535 0.9011 86 0.9222 0.8652 0.8928 178 0.9612 0.9688 0.9650 128 0.9184 0.9184 0.9184 0.9846
0.0293 26.0 2496 0.0473 0.9101 0.9419 0.9257 86 0.9157 0.9157 0.9157 178 0.9767 0.9844 0.9805 128 0.9343 0.9439 0.9391 0.9868
0.0279 27.0 2592 0.0473 0.8791 0.9302 0.9040 86 0.9061 0.9213 0.9136 178 0.9688 0.9688 0.9688 128 0.92 0.9388 0.9293 0.9870
0.0273 28.0 2688 0.0466 0.9 0.9419 0.9205 86 0.9270 0.9270 0.9270 178 0.9688 0.9688 0.9688 128 0.9343 0.9439 0.9391 0.9876
0.0259 29.0 2784 0.0479 0.8791 0.9302 0.9040 86 0.9368 0.9157 0.9261 178 0.9688 0.9688 0.9688 128 0.9338 0.9362 0.9350 0.9868
0.0253 30.0 2880 0.0495 0.8817 0.9535 0.9162 86 0.8977 0.8876 0.8927 178 0.9615 0.9766 0.9690 128 0.9148 0.9311 0.9229 0.9860
0.0245 31.0 2976 0.0515 0.8913 0.9535 0.9213 86 0.9408 0.8933 0.9164 178 0.9766 0.9766 0.9766 128 0.9409 0.9337 0.9373 0.9860
0.0229 32.0 3072 0.0516 0.8737 0.9651 0.9171 86 0.9302 0.8989 0.9143 178 0.9612 0.9688 0.9650 128 0.9268 0.9362 0.9315 0.9870
0.0215 33.0 3168 0.0465 0.8817 0.9535 0.9162 86 0.9415 0.9045 0.9226 178 0.9766 0.9766 0.9766 128 0.9388 0.9388 0.9388 0.9879
0.0232 34.0 3264 0.0509 0.8791 0.9302 0.9040 86 0.9535 0.9213 0.9371 178 0.9612 0.9688 0.9650 128 0.9388 0.9388 0.9388 0.9881
0.0223 35.0 3360 0.0558 0.8632 0.9535 0.9061 86 0.9639 0.8989 0.9302 178 0.9612 0.9688 0.9650 128 0.9385 0.9337 0.9361 0.9865
0.0223 36.0 3456 0.0532 0.8646 0.9651 0.9121 86 0.9471 0.9045 0.9253 178 0.9766 0.9766 0.9766 128 0.9365 0.9413 0.9389 0.9876
0.0202 37.0 3552 0.0514 0.8804 0.9419 0.9101 86 0.9527 0.9045 0.9280 178 0.9615 0.9766 0.9690 128 0.9386 0.9362 0.9374 0.9870
0.0188 38.0 3648 0.0515 0.8646 0.9651 0.9121 86 0.9532 0.9157 0.9341 178 0.9615 0.9766 0.9690 128 0.9345 0.9464 0.9404 0.9870
0.0199 39.0 3744 0.0418 0.8989 0.9302 0.9143 86 0.9266 0.9213 0.9239 178 0.9690 0.9766 0.9728 128 0.9342 0.9413 0.9377 0.9892
0.0178 40.0 3840 0.0537 0.9 0.9419 0.9205 86 0.9419 0.9101 0.9257 178 0.9612 0.9688 0.9650 128 0.9386 0.9362 0.9374 0.9887
0.0178 41.0 3936 0.0538 0.8817 0.9535 0.9162 86 0.9527 0.9045 0.9280 178 0.9612 0.9688 0.9650 128 0.9386 0.9362 0.9374 0.9870
0.0174 42.0 4032 0.0477 0.9011 0.9535 0.9266 86 0.9425 0.9213 0.9318 178 0.9688 0.9688 0.9688 128 0.9415 0.9439 0.9427 0.9895
0.0169 43.0 4128 0.0579 0.8913 0.9535 0.9213 86 0.9467 0.8989 0.9222 178 0.9535 0.9609 0.9572 128 0.9359 0.9311 0.9335 0.9865
0.0173 44.0 4224 0.0553 0.8660 0.9767 0.9180 86 0.9524 0.8989 0.9249 178 0.9766 0.9766 0.9766 128 0.9389 0.9413 0.9401 0.9865
0.0163 45.0 4320 0.0470 0.9022 0.9651 0.9326 86 0.9763 0.9270 0.9510 178 0.9766 0.9766 0.9766 128 0.9589 0.9515 0.9552 0.9889
0.0152 46.0 4416 0.0626 0.8660 0.9767 0.9180 86 0.9639 0.8989 0.9302 178 0.9688 0.9688 0.9688 128 0.9412 0.9388 0.9400 0.9873
0.0156 47.0 4512 0.0596 0.8557 0.9651 0.9071 86 0.9249 0.8989 0.9117 178 0.9612 0.9688 0.9650 128 0.9198 0.9362 0.9279 0.9862
0.0154 48.0 4608 0.0501 0.9111 0.9535 0.9318 86 0.9535 0.9213 0.9371 178 0.9766 0.9766 0.9766 128 0.9513 0.9464 0.9488 0.9887
0.0166 49.0 4704 0.0430 0.9121 0.9651 0.9379 86 0.9205 0.9101 0.9153 178 0.9764 0.9688 0.9725 128 0.9365 0.9413 0.9389 0.9900
0.0147 50.0 4800 0.0513 0.8913 0.9535 0.9213 86 0.9535 0.9213 0.9371 178 0.9843 0.9766 0.9804 128 0.9488 0.9464 0.9476 0.9889
0.0161 51.0 4896 0.0482 0.8723 0.9535 0.9111 86 0.9310 0.9101 0.9205 178 0.9688 0.9688 0.9688 128 0.9293 0.9388 0.9340 0.9879
0.0138 52.0 4992 0.0492 0.8842 0.9767 0.9282 86 0.9419 0.9101 0.9257 178 0.9688 0.9688 0.9688 128 0.9367 0.9439 0.9403 0.9879
0.0155 53.0 5088 0.0560 0.8830 0.9651 0.9222 86 0.9474 0.9101 0.9284 178 0.9688 0.9688 0.9688 128 0.9389 0.9413 0.9401 0.9881
0.014 54.0 5184 0.0483 0.8925 0.9651 0.9274 86 0.9368 0.9157 0.9261 178 0.9688 0.9688 0.9688 128 0.9367 0.9439 0.9403 0.9879
0.0125 55.0 5280 0.0537 0.8842 0.9767 0.9282 86 0.9419 0.9101 0.9257 178 0.9688 0.9688 0.9688 128 0.9367 0.9439 0.9403 0.9870
0.0133 56.0 5376 0.0531 0.8737 0.9651 0.9171 86 0.9360 0.9045 0.9200 178 0.9688 0.9688 0.9688 128 0.9316 0.9388 0.9352 0.9860
0.012 57.0 5472 0.0531 0.8830 0.9651 0.9222 86 0.9310 0.9101 0.9205 178 0.9612 0.9688 0.9650 128 0.9295 0.9413 0.9354 0.9876
0.0113 58.0 5568 0.0546 0.8901 0.9419 0.9153 86 0.9415 0.9045 0.9226 178 0.9766 0.9766 0.9766 128 0.9410 0.9362 0.9386 0.9879
0.0118 59.0 5664 0.0570 0.8681 0.9186 0.8927 86 0.92 0.9045 0.9122 178 0.9764 0.9688 0.9725 128 0.9262 0.9286 0.9274 0.9862
0.0115 60.0 5760 0.0717 0.8737 0.9651 0.9171 86 0.9464 0.8933 0.9191 178 0.9688 0.9688 0.9688 128 0.9361 0.9337 0.9349 0.9865
0.0119 61.0 5856 0.0595 0.8817 0.9535 0.9162 86 0.9643 0.9101 0.9364 178 0.9764 0.9688 0.9725 128 0.9485 0.9388 0.9436 0.9876
0.0097 62.0 5952 0.0688 0.8936 0.9767 0.9333 86 0.9701 0.9101 0.9391 178 0.9764 0.9688 0.9725 128 0.9536 0.9439 0.9487 0.9873
0.0107 63.0 6048 0.0602 0.8936 0.9767 0.9333 86 0.9364 0.9101 0.9231 178 0.9688 0.9688 0.9688 128 0.9367 0.9439 0.9403 0.9868
0.0118 64.0 6144 0.0608 0.8817 0.9535 0.9162 86 0.9643 0.9101 0.9364 178 0.9688 0.9688 0.9688 128 0.9460 0.9388 0.9424 0.9868
0.0101 65.0 6240 0.0554 0.8913 0.9535 0.9213 86 0.9480 0.9213 0.9345 178 0.9688 0.9688 0.9688 128 0.9415 0.9439 0.9427 0.9884
0.011 66.0 6336 0.0612 0.8571 0.9767 0.9130 86 0.9310 0.9101 0.9205 178 0.9538 0.9688 0.9612 128 0.9204 0.9439 0.9320 0.9862
0.0096 67.0 6432 0.0567 0.9022 0.9651 0.9326 86 0.9591 0.9213 0.9398 178 0.9688 0.9688 0.9688 128 0.9488 0.9464 0.9476 0.9879
0.0101 68.0 6528 0.0614 0.8842 0.9767 0.9282 86 0.9702 0.9157 0.9422 178 0.9688 0.9688 0.9688 128 0.9488 0.9464 0.9476 0.9873
0.0095 69.0 6624 0.0630 0.8842 0.9767 0.9282 86 0.9586 0.9101 0.9337 178 0.9688 0.9688 0.9688 128 0.9439 0.9439 0.9439 0.9873
0.0087 70.0 6720 0.0570 0.875 0.9767 0.9231 86 0.9532 0.9157 0.9341 178 0.9688 0.9688 0.9688 128 0.9392 0.9464 0.9428 0.9889
0.0104 71.0 6816 0.0534 0.8830 0.9651 0.9222 86 0.9429 0.9270 0.9348 178 0.9688 0.9688 0.9688 128 0.9370 0.9490 0.9430 0.9895
0.0097 72.0 6912 0.0604 0.8925 0.9651 0.9274 86 0.9820 0.9213 0.9507 178 0.9766 0.9766 0.9766 128 0.9588 0.9490 0.9538 0.9881
0.0092 73.0 7008 0.0575 0.875 0.9767 0.9231 86 0.9477 0.9157 0.9314 178 0.9766 0.9766 0.9766 128 0.9394 0.9490 0.9442 0.9887
0.0102 74.0 7104 0.0591 0.875 0.9767 0.9231 86 0.9527 0.9045 0.9280 178 0.9766 0.9766 0.9766 128 0.9415 0.9439 0.9427 0.9876
0.0091 75.0 7200 0.0529 0.8737 0.9651 0.9171 86 0.9480 0.9213 0.9345 178 0.9766 0.9766 0.9766 128 0.9394 0.9490 0.9442 0.9884
0.0096 76.0 7296 0.0574 0.8660 0.9767 0.9180 86 0.9702 0.9157 0.9422 178 0.9766 0.9766 0.9766 128 0.9466 0.9490 0.9478 0.9868
0.0077 77.0 7392 0.0576 0.8710 0.9419 0.9050 86 0.9483 0.9270 0.9375 178 0.9766 0.9766 0.9766 128 0.9392 0.9464 0.9428 0.9881
0.0084 78.0 7488 0.0663 0.8842 0.9767 0.9282 86 0.9641 0.9045 0.9333 178 0.9766 0.9766 0.9766 128 0.9487 0.9439 0.9463 0.9868
0.0086 79.0 7584 0.0603 0.8842 0.9767 0.9282 86 0.9467 0.8989 0.9222 178 0.9766 0.9766 0.9766 128 0.9413 0.9413 0.9413 0.9876
0.0096 80.0 7680 0.0587 0.875 0.9767 0.9231 86 0.9529 0.9101 0.9310 178 0.9766 0.9766 0.9766 128 0.9416 0.9464 0.9440 0.9884
0.0084 81.0 7776 0.0572 0.8925 0.9651 0.9274 86 0.9702 0.9157 0.9422 178 0.9766 0.9766 0.9766 128 0.9537 0.9464 0.9501 0.9879
0.0083 82.0 7872 0.0594 0.8842 0.9767 0.9282 86 0.9645 0.9157 0.9395 178 0.9766 0.9766 0.9766 128 0.9490 0.9490 0.9490 0.9881
0.0067 83.0 7968 0.0607 0.8913 0.9535 0.9213 86 0.9701 0.9101 0.9391 178 0.9766 0.9766 0.9766 128 0.9535 0.9413 0.9474 0.9873
0.0075 84.0 8064 0.0596 0.875 0.9767 0.9231 86 0.9477 0.9157 0.9314 178 0.9766 0.9766 0.9766 128 0.9394 0.9490 0.9442 0.9879
0.0086 85.0 8160 0.0574 0.8830 0.9651 0.9222 86 0.9477 0.9157 0.9314 178 0.9766 0.9766 0.9766 128 0.9416 0.9464 0.9440 0.9881
0.0075 86.0 8256 0.0580 0.8842 0.9767 0.9282 86 0.9762 0.9213 0.9480 178 0.9766 0.9766 0.9766 128 0.9540 0.9515 0.9527 0.9884
0.0073 87.0 8352 0.0555 0.8830 0.9651 0.9222 86 0.9480 0.9213 0.9345 178 0.9766 0.9766 0.9766 128 0.9418 0.9490 0.9454 0.9889
0.007 88.0 8448 0.0541 0.8913 0.9535 0.9213 86 0.9480 0.9213 0.9345 178 0.9766 0.9766 0.9766 128 0.9440 0.9464 0.9452 0.9887
0.0072 89.0 8544 0.0546 0.8830 0.9651 0.9222 86 0.9532 0.9157 0.9341 178 0.9766 0.9766 0.9766 128 0.9440 0.9464 0.9452 0.9887
0.0061 90.0 8640 0.0586 0.8830 0.9651 0.9222 86 0.9643 0.9101 0.9364 178 0.9766 0.9766 0.9766 128 0.9487 0.9439 0.9463 0.9876
0.0075 91.0 8736 0.0576 0.8830 0.9651 0.9222 86 0.9643 0.9101 0.9364 178 0.9766 0.9766 0.9766 128 0.9487 0.9439 0.9463 0.9879
0.0077 92.0 8832 0.0568 0.8925 0.9651 0.9274 86 0.9529 0.9101 0.9310 178 0.9766 0.9766 0.9766 128 0.9463 0.9439 0.9451 0.9887
0.0068 93.0 8928 0.0587 0.8925 0.9651 0.9274 86 0.9701 0.9101 0.9391 178 0.9766 0.9766 0.9766 128 0.9536 0.9439 0.9487 0.9873
0.0063 94.0 9024 0.0604 0.8842 0.9767 0.9282 86 0.9588 0.9157 0.9368 178 0.9690 0.9766 0.9728 128 0.9442 0.9490 0.9466 0.9884
0.0065 95.0 9120 0.0611 0.8842 0.9767 0.9282 86 0.9759 0.9101 0.9419 178 0.9766 0.9766 0.9766 128 0.9537 0.9464 0.9501 0.9876
0.0058 96.0 9216 0.0611 0.8842 0.9767 0.9282 86 0.9701 0.9101 0.9391 178 0.9766 0.9766 0.9766 128 0.9513 0.9464 0.9488 0.9876
0.007 97.0 9312 0.0622 0.8830 0.9651 0.9222 86 0.9586 0.9101 0.9337 178 0.9766 0.9766 0.9766 128 0.9463 0.9439 0.9451 0.9870
0.0069 98.0 9408 0.0621 0.8925 0.9651 0.9274 86 0.9701 0.9101 0.9391 178 0.9766 0.9766 0.9766 128 0.9536 0.9439 0.9487 0.9873
0.0067 99.0 9504 0.0630 0.8830 0.9651 0.9222 86 0.9641 0.9045 0.9333 178 0.9766 0.9766 0.9766 128 0.9486 0.9413 0.9449 0.9870
0.0076 100.0 9600 0.0628 0.8830 0.9651 0.9222 86 0.9641 0.9045 0.9333 178 0.9766 0.9766 0.9766 128 0.9486 0.9413 0.9449 0.9870

Framework versions

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