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nerui-base-0

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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: nerui-base-0
    results: []

nerui-base-0

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: 0.1036
  • Location Precision: 0.9278
  • Location Recall: 0.9574
  • Location F1: 0.9424
  • Location Number: 94
  • Organization Precision: 0.95
  • Organization Recall: 0.9102
  • Organization F1: 0.9297
  • Organization Number: 167
  • Person Precision: 0.9851
  • Person Recall: 0.9635
  • Person F1: 0.9742
  • Person Number: 137
  • Overall Precision: 0.9565
  • Overall Recall: 0.9397
  • Overall F1: 0.9480
  • Overall Accuracy: 0.9892

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
0.2611 1.0 96 0.0463 0.8969 0.9255 0.9110 94 0.8837 0.9102 0.8968 167 0.9854 0.9854 0.9854 137 0.9212 0.9397 0.9303 0.9865
0.0645 2.0 192 0.0678 0.7627 0.9574 0.8491 94 0.8758 0.8443 0.8598 167 0.9925 0.9708 0.9815 137 0.8814 0.9146 0.8977 0.9779
0.0354 3.0 288 0.0467 0.9 0.9574 0.9278 94 0.8935 0.9042 0.8988 167 0.9783 0.9854 0.9818 137 0.9238 0.9447 0.9342 0.9862
0.0232 4.0 384 0.0635 0.8911 0.9574 0.9231 94 0.9487 0.8862 0.9164 167 0.9771 0.9343 0.9552 137 0.9433 0.9196 0.9313 0.9845
0.0158 5.0 480 0.0530 0.8585 0.9681 0.91 94 0.9533 0.8563 0.9022 167 0.9854 0.9854 0.9854 137 0.9389 0.9271 0.9330 0.9862
0.011 6.0 576 0.0508 0.9175 0.9468 0.9319 94 0.9157 0.9102 0.9129 167 0.9853 0.9781 0.9817 137 0.9398 0.9422 0.9410 0.9878
0.0086 7.0 672 0.0657 0.9255 0.9255 0.9255 94 0.9017 0.9341 0.9176 167 0.9853 0.9781 0.9817 137 0.9355 0.9472 0.9413 0.9865
0.007 8.0 768 0.0754 0.8866 0.9149 0.9005 94 0.8935 0.9042 0.8988 167 0.9852 0.9708 0.9779 137 0.9227 0.9296 0.9262 0.9865
0.0061 9.0 864 0.0703 0.9231 0.8936 0.9081 94 0.8729 0.9461 0.9080 167 1.0 0.9781 0.9889 137 0.9261 0.9447 0.9353 0.9878
0.0058 10.0 960 0.0650 0.9130 0.8936 0.9032 94 0.8757 0.9281 0.9012 167 0.9708 0.9708 0.9708 137 0.9163 0.9347 0.9254 0.9867
0.0048 11.0 1056 0.0849 0.8812 0.9468 0.9128 94 0.9006 0.9222 0.9112 167 0.9851 0.9635 0.9742 137 0.9236 0.9422 0.9328 0.9859
0.0057 12.0 1152 0.0725 0.8969 0.9255 0.9110 94 0.8851 0.9222 0.9032 167 1.0 0.9781 0.9889 137 0.9259 0.9422 0.9340 0.9870
0.0052 13.0 1248 0.0872 0.9333 0.8936 0.9130 94 0.8869 0.8922 0.8896 167 0.9853 0.9781 0.9817 137 0.9315 0.9221 0.9268 0.9845
0.002 14.0 1344 0.0797 0.9121 0.8830 0.8973 94 0.9231 0.9341 0.9286 167 0.9853 0.9781 0.9817 137 0.9419 0.9372 0.9395 0.9881
0.0036 15.0 1440 0.0880 0.9451 0.9149 0.9297 94 0.9075 0.9401 0.9235 167 1.0 0.9781 0.9889 137 0.9472 0.9472 0.9472 0.9873
0.0026 16.0 1536 0.0871 0.8842 0.8936 0.8889 94 0.9390 0.9222 0.9305 167 0.9852 0.9708 0.9779 137 0.9416 0.9322 0.9369 0.9870
0.0028 17.0 1632 0.0821 0.89 0.9468 0.9175 94 0.9277 0.9222 0.9249 167 1.0 0.9708 0.9852 137 0.9424 0.9447 0.9435 0.9884
0.0024 18.0 1728 0.0746 0.8980 0.9362 0.9167 94 0.9394 0.9281 0.9337 167 0.9925 0.9635 0.9778 137 0.9470 0.9422 0.9446 0.9890
0.003 19.0 1824 0.0849 0.88 0.9362 0.9072 94 0.9207 0.9042 0.9124 167 0.9706 0.9635 0.9670 137 0.9275 0.9322 0.9298 0.9859
0.0035 20.0 1920 0.0830 0.87 0.9255 0.8969 94 0.9444 0.9162 0.9301 167 0.9925 0.9708 0.9815 137 0.9419 0.9372 0.9395 0.9876
0.0015 21.0 2016 0.0965 0.8947 0.9043 0.8995 94 0.9172 0.9281 0.9226 167 0.9851 0.9635 0.9742 137 0.9347 0.9347 0.9347 0.9865
0.0029 22.0 2112 0.1119 0.8947 0.9043 0.8995 94 0.9006 0.9222 0.9112 167 0.9496 0.9635 0.9565 137 0.9160 0.9322 0.9240 0.9831
0.0031 23.0 2208 0.1021 0.8932 0.9787 0.9340 94 0.9527 0.8443 0.8952 167 0.9638 0.9708 0.9673 137 0.9409 0.9196 0.9301 0.9843
0.0023 24.0 2304 0.0873 0.8725 0.9468 0.9082 94 0.9207 0.9042 0.9124 167 0.9779 0.9708 0.9744 137 0.9279 0.9372 0.9325 0.9865
0.0029 25.0 2400 0.1052 0.8571 0.9574 0.9045 94 0.9030 0.8922 0.8976 167 0.9781 0.9781 0.9781 137 0.9165 0.9372 0.9267 0.9856
0.0033 26.0 2496 0.1222 0.7946 0.9468 0.8641 94 0.9419 0.8743 0.9068 167 0.9708 0.9708 0.9708 137 0.9109 0.9246 0.9177 0.9829
0.0021 27.0 2592 0.1137 0.8641 0.9468 0.9036 94 0.9202 0.8982 0.9091 167 0.9708 0.9708 0.9708 137 0.9231 0.9347 0.9288 0.9854
0.0014 28.0 2688 0.0999 0.8854 0.9043 0.8947 94 0.8953 0.9222 0.9086 167 0.9850 0.9562 0.9704 137 0.9227 0.9296 0.9262 0.9862
0.0017 29.0 2784 0.0964 0.8854 0.9043 0.8947 94 0.8935 0.9042 0.8988 167 0.9571 0.9781 0.9675 137 0.9136 0.9296 0.9215 0.9843
0.0064 30.0 2880 0.0691 0.8854 0.9043 0.8947 94 0.9235 0.9401 0.9318 167 0.9925 0.9635 0.9778 137 0.9373 0.9397 0.9385 0.9876
0.0032 31.0 2976 0.0872 0.8980 0.9362 0.9167 94 0.9075 0.9401 0.9235 167 1.0 0.9708 0.9852 137 0.9356 0.9497 0.9426 0.9878
0.0027 32.0 3072 0.0921 0.8889 0.9362 0.9119 94 0.9118 0.9281 0.9199 167 0.9850 0.9562 0.9704 137 0.9303 0.9397 0.9350 0.9862
0.0017 33.0 3168 0.0955 0.8878 0.9255 0.9062 94 0.9448 0.9222 0.9333 167 0.9776 0.9562 0.9668 137 0.9418 0.9347 0.9382 0.9870
0.0027 34.0 3264 0.1089 0.8835 0.9681 0.9239 94 0.9509 0.9281 0.9394 167 0.9852 0.9708 0.9779 137 0.9451 0.9523 0.9487 0.9867
0.0024 35.0 3360 0.0920 0.8738 0.9574 0.9137 94 0.9451 0.9281 0.9366 167 0.9640 0.9781 0.9710 137 0.9335 0.9523 0.9428 0.9870
0.0022 36.0 3456 0.0792 0.9192 0.9681 0.9430 94 0.9625 0.9222 0.9419 167 0.9638 0.9708 0.9673 137 0.9521 0.9497 0.9509 0.9898
0.0013 37.0 3552 0.0962 0.8911 0.9574 0.9231 94 0.9509 0.9281 0.9394 167 0.9925 0.9708 0.9815 137 0.9497 0.9497 0.9497 0.9884
0.0028 38.0 3648 0.0811 0.9091 0.9574 0.9326 94 0.9123 0.9341 0.9231 167 0.9850 0.9562 0.9704 137 0.9355 0.9472 0.9413 0.9876
0.0022 39.0 3744 0.1019 0.8788 0.9255 0.9016 94 0.9162 0.9162 0.9162 167 0.9850 0.9562 0.9704 137 0.9298 0.9322 0.9310 0.9859
0.0012 40.0 3840 0.0960 0.8889 0.9362 0.9119 94 0.8971 0.9401 0.9181 167 0.9925 0.9635 0.9778 137 0.9263 0.9472 0.9366 0.9867
0.0008 41.0 3936 0.0964 0.8922 0.9681 0.9286 94 0.9682 0.9102 0.9383 167 0.9852 0.9708 0.9779 137 0.9543 0.9447 0.9495 0.9890
0.0015 42.0 4032 0.0783 0.9175 0.9468 0.9319 94 0.9048 0.9102 0.9075 167 0.9708 0.9708 0.9708 137 0.9303 0.9397 0.9350 0.9881
0.0019 43.0 4128 0.0777 0.8932 0.9787 0.9340 94 0.9387 0.9162 0.9273 167 0.9925 0.9708 0.9815 137 0.945 0.9497 0.9474 0.9884
0.0011 44.0 4224 0.0826 0.8762 0.9787 0.9246 94 0.9568 0.9281 0.9422 167 0.9851 0.9635 0.9742 137 0.9451 0.9523 0.9487 0.9892
0.0007 45.0 4320 0.0795 0.9020 0.9787 0.9388 94 0.9554 0.8982 0.9259 167 0.9778 0.9635 0.9706 137 0.9492 0.9397 0.9444 0.9867
0.0025 46.0 4416 0.0816 0.9109 0.9787 0.9436 94 0.9012 0.9281 0.9145 167 0.9924 0.9562 0.9740 137 0.9333 0.9497 0.9415 0.9878
0.0012 47.0 4512 0.0946 0.8692 0.9894 0.9254 94 0.9620 0.9102 0.9354 167 0.9925 0.9635 0.9778 137 0.9472 0.9472 0.9472 0.9876
0.0016 48.0 4608 0.0961 0.8762 0.9787 0.9246 94 0.9277 0.9222 0.9249 167 0.9925 0.9635 0.9778 137 0.9356 0.9497 0.9426 0.9873
0.001 49.0 4704 0.0995 0.9010 0.9681 0.9333 94 0.9231 0.9341 0.9286 167 0.9925 0.9708 0.9815 137 0.9406 0.9548 0.9476 0.9865
0.001 50.0 4800 0.0989 0.8932 0.9787 0.9340 94 0.9554 0.8982 0.9259 167 0.9850 0.9562 0.9704 137 0.9491 0.9372 0.9431 0.9870
0.0004 51.0 4896 0.1130 0.9020 0.9787 0.9388 94 0.9264 0.9042 0.9152 167 0.9779 0.9708 0.9744 137 0.9377 0.9447 0.9412 0.9870
0.0007 52.0 4992 0.1079 0.91 0.9681 0.9381 94 0.9325 0.9102 0.9212 167 0.9779 0.9708 0.9744 137 0.9424 0.9447 0.9435 0.9878
0.0011 53.0 5088 0.1021 0.9286 0.9681 0.9479 94 0.9437 0.9042 0.9235 167 0.9778 0.9635 0.9706 137 0.9517 0.9397 0.9456 0.9878
0.0009 54.0 5184 0.1243 0.8776 0.9149 0.8958 94 0.875 0.9222 0.8980 167 0.9778 0.9635 0.9706 137 0.9095 0.9347 0.9219 0.9826
0.0011 55.0 5280 0.0882 0.91 0.9681 0.9381 94 0.9162 0.9162 0.9162 167 0.9851 0.9635 0.9742 137 0.9377 0.9447 0.9412 0.9884
0.0004 56.0 5376 0.0880 0.9286 0.9681 0.9479 94 0.9437 0.9042 0.9235 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9901
0.0006 57.0 5472 0.1010 0.9010 0.9681 0.9333 94 0.9059 0.9222 0.9139 167 0.9851 0.9635 0.9742 137 0.9309 0.9472 0.9390 0.9873
0.0006 58.0 5568 0.0980 0.9010 0.9681 0.9333 94 0.9112 0.9222 0.9167 167 0.9852 0.9708 0.9779 137 0.9333 0.9497 0.9415 0.9876
0.0003 59.0 5664 0.0993 0.9192 0.9681 0.9430 94 0.9497 0.9042 0.9264 167 0.9778 0.9635 0.9706 137 0.9517 0.9397 0.9456 0.9884
0.0003 60.0 5760 0.0983 0.9 0.9574 0.9278 94 0.9273 0.9162 0.9217 167 0.9852 0.9708 0.9779 137 0.94 0.9447 0.9424 0.9884
0.0003 61.0 5856 0.0937 0.91 0.9681 0.9381 94 0.9096 0.9042 0.9069 167 0.9851 0.9635 0.9742 137 0.935 0.9397 0.9373 0.9887
0.0011 62.0 5952 0.1109 0.8835 0.9681 0.9239 94 0.9497 0.9042 0.9264 167 0.9925 0.9708 0.9815 137 0.9470 0.9422 0.9446 0.9867
0.0009 63.0 6048 0.0866 0.9286 0.9681 0.9479 94 0.9162 0.9162 0.9162 167 0.9925 0.9635 0.9778 137 0.9447 0.9447 0.9447 0.9898
0.0004 64.0 6144 0.1202 0.88 0.9362 0.9072 94 0.9222 0.9222 0.9222 167 0.9925 0.9635 0.9778 137 0.935 0.9397 0.9373 0.9848
0.0023 65.0 6240 0.0968 0.9293 0.9787 0.9534 94 0.9217 0.9162 0.9189 167 0.9926 0.9781 0.9853 137 0.9475 0.9523 0.9499 0.9884
0.0017 66.0 6336 0.1031 0.9192 0.9681 0.9430 94 0.9444 0.9162 0.9301 167 0.9925 0.9708 0.9815 137 0.9544 0.9472 0.9508 0.9876
0.0014 67.0 6432 0.1050 0.9091 0.9574 0.9326 94 0.9497 0.9042 0.9264 167 0.9925 0.9708 0.9815 137 0.9541 0.9397 0.9468 0.9881
0.0007 68.0 6528 0.1049 0.9192 0.9681 0.9430 94 0.9554 0.8982 0.9259 167 1.0 0.9708 0.9852 137 0.9614 0.9397 0.9504 0.9892
0.0005 69.0 6624 0.0997 0.9184 0.9574 0.9375 94 0.9112 0.9222 0.9167 167 0.9851 0.9635 0.9742 137 0.9377 0.9447 0.9412 0.9859
0.001 70.0 6720 0.1054 0.9184 0.9574 0.9375 94 0.9118 0.9281 0.9199 167 0.9851 0.9635 0.9742 137 0.9378 0.9472 0.9425 0.9876
0.0005 71.0 6816 0.0978 0.9192 0.9681 0.9430 94 0.9563 0.9162 0.9358 167 0.9851 0.9635 0.9742 137 0.9567 0.9447 0.9507 0.9901
0.0008 72.0 6912 0.0955 0.9271 0.9468 0.9368 94 0.9387 0.9162 0.9273 167 0.9851 0.9635 0.9742 137 0.9517 0.9397 0.9456 0.9887
0.0005 73.0 7008 0.1008 0.9278 0.9574 0.9424 94 0.9503 0.9162 0.9329 167 0.9851 0.9635 0.9742 137 0.9566 0.9422 0.9494 0.9892
0.0004 74.0 7104 0.1033 0.9278 0.9574 0.9424 94 0.95 0.9102 0.9297 167 0.9776 0.9562 0.9668 137 0.9540 0.9372 0.9455 0.9884
0.0005 75.0 7200 0.1130 0.9278 0.9574 0.9424 94 0.9618 0.9042 0.9321 167 0.9850 0.9562 0.9704 137 0.9612 0.9347 0.9478 0.9887
0.0007 76.0 7296 0.1115 0.9278 0.9574 0.9424 94 0.9329 0.9162 0.9245 167 0.9776 0.9562 0.9668 137 0.9468 0.9397 0.9433 0.9884
0.0006 77.0 7392 0.1130 0.9278 0.9574 0.9424 94 0.9554 0.8982 0.9259 167 0.9852 0.9708 0.9779 137 0.9589 0.9372 0.9479 0.9890
0.0005 78.0 7488 0.1151 0.9278 0.9574 0.9424 94 0.9371 0.8922 0.9141 167 0.9704 0.9562 0.9632 137 0.9463 0.9296 0.9379 0.9876
0.0003 79.0 7584 0.1110 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9887
0.0002 80.0 7680 0.1127 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9887
0.0003 81.0 7776 0.1135 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9887
0.0003 82.0 7872 0.1082 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9887
0.0006 83.0 7968 0.1155 0.9192 0.9681 0.9430 94 0.9742 0.9042 0.9379 167 0.9852 0.9708 0.9779 137 0.9640 0.9422 0.9530 0.9895
0.0003 84.0 8064 0.1072 0.9286 0.9681 0.9479 94 0.9623 0.9162 0.9387 167 0.9851 0.9635 0.9742 137 0.9616 0.9447 0.9531 0.9898
0.0007 85.0 8160 0.1013 0.9278 0.9574 0.9424 94 0.9387 0.9162 0.9273 167 0.9851 0.9635 0.9742 137 0.9518 0.9422 0.9470 0.9895
0.0003 86.0 8256 0.1022 0.9278 0.9574 0.9424 94 0.9444 0.9162 0.9301 167 0.9851 0.9635 0.9742 137 0.9542 0.9422 0.9482 0.9898
0.0002 87.0 8352 0.1026 0.9278 0.9574 0.9424 94 0.9444 0.9162 0.9301 167 0.9851 0.9635 0.9742 137 0.9542 0.9422 0.9482 0.9898
0.0002 88.0 8448 0.1029 0.9278 0.9574 0.9424 94 0.9444 0.9162 0.9301 167 0.9851 0.9635 0.9742 137 0.9542 0.9422 0.9482 0.9898
0.0003 89.0 8544 0.1034 0.9278 0.9574 0.9424 94 0.9444 0.9162 0.9301 167 0.9851 0.9635 0.9742 137 0.9542 0.9422 0.9482 0.9898
0.0003 90.0 8640 0.1043 0.9278 0.9574 0.9424 94 0.9563 0.9162 0.9358 167 0.9851 0.9635 0.9742 137 0.9591 0.9422 0.9506 0.9898
0.0002 91.0 8736 0.1045 0.9278 0.9574 0.9424 94 0.95 0.9102 0.9297 167 0.9851 0.9635 0.9742 137 0.9565 0.9397 0.9480 0.9892
0.0002 92.0 8832 0.1047 0.9278 0.9574 0.9424 94 0.9503 0.9162 0.9329 167 0.9851 0.9635 0.9742 137 0.9566 0.9422 0.9494 0.9895
0.0003 93.0 8928 0.1054 0.9278 0.9574 0.9424 94 0.95 0.9102 0.9297 167 0.9851 0.9635 0.9742 137 0.9565 0.9397 0.9480 0.9898
0.0009 94.0 9024 0.1089 0.9278 0.9574 0.9424 94 0.9560 0.9102 0.9325 167 0.9851 0.9635 0.9742 137 0.9590 0.9397 0.9492 0.9895
0.0004 95.0 9120 0.1033 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9895
0.0002 96.0 9216 0.1028 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9895
0.0002 97.0 9312 0.1030 0.9278 0.9574 0.9424 94 0.9441 0.9102 0.9268 167 0.9851 0.9635 0.9742 137 0.9541 0.9397 0.9468 0.9895
0.0003 98.0 9408 0.1035 0.9278 0.9574 0.9424 94 0.95 0.9102 0.9297 167 0.9851 0.9635 0.9742 137 0.9565 0.9397 0.9480 0.9892
0.0002 99.0 9504 0.1036 0.9278 0.9574 0.9424 94 0.95 0.9102 0.9297 167 0.9851 0.9635 0.9742 137 0.9565 0.9397 0.9480 0.9892
0.0002 100.0 9600 0.1036 0.9278 0.9574 0.9424 94 0.95 0.9102 0.9297 167 0.9851 0.9635 0.9742 137 0.9565 0.9397 0.9480 0.9892

Framework versions

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