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nerui-pt-pl10-1

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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: nerui-pt-pl10-1
    results: []

nerui-pt-pl10-1

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: 0.0479
  • Location Precision: 0.9316
  • Location Recall: 0.9397
  • Location F1: 0.9356
  • Location Number: 116
  • Organization Precision: 0.9477
  • Organization Recall: 0.9177
  • Organization F1: 0.9325
  • Organization Number: 158
  • Person Precision: 0.9683
  • Person Recall: 0.9839
  • Person F1: 0.976
  • Person Number: 124
  • Overall Precision: 0.9495
  • Overall Recall: 0.9447
  • Overall F1: 0.9471
  • Overall Accuracy: 0.9898

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
0.8279 1.0 96 0.3868 0.2857 0.0345 0.0615 116 0.2222 0.3797 0.2804 158 0.25 0.3065 0.2754 124 0.2339 0.2563 0.2446 0.8677
0.3613 2.0 192 0.2065 0.3721 0.4138 0.3918 116 0.5906 0.6392 0.6140 158 0.5141 0.7339 0.6047 124 0.5031 0.6030 0.5486 0.9347
0.1915 3.0 288 0.0954 0.8447 0.75 0.7945 116 0.7234 0.8608 0.7861 158 0.9242 0.9839 0.9531 124 0.8156 0.8668 0.8404 0.9704
0.1356 4.0 384 0.0816 0.7609 0.9052 0.8268 116 0.7977 0.8734 0.8338 158 0.9462 0.9919 0.9685 124 0.8299 0.9196 0.8725 0.9717
0.1094 5.0 480 0.0581 0.9009 0.8621 0.8811 116 0.8679 0.8734 0.8707 158 0.9685 0.9919 0.9801 124 0.9093 0.9070 0.9082 0.9811
0.1026 6.0 576 0.0524 0.8425 0.9224 0.8807 116 0.9452 0.8734 0.9079 158 0.9609 0.9919 0.9762 124 0.9177 0.9246 0.9212 0.9838
0.0877 7.0 672 0.0449 0.9091 0.8621 0.8850 116 0.8706 0.9367 0.9024 158 0.9762 0.9919 0.9840 124 0.9138 0.9322 0.9229 0.9844
0.0774 8.0 768 0.0418 0.9024 0.9569 0.9289 116 0.9236 0.9177 0.9206 158 0.9762 0.9919 0.9840 124 0.9335 0.9523 0.9428 0.9863
0.0735 9.0 864 0.0368 0.9 0.9310 0.9153 116 0.9207 0.9557 0.9379 158 0.9762 0.9919 0.9840 124 0.9317 0.9598 0.9455 0.9887
0.0657 10.0 960 0.0412 0.8926 0.9310 0.9114 116 0.9423 0.9304 0.9363 158 0.9462 0.9919 0.9685 124 0.9287 0.9497 0.9391 0.9865
0.0605 11.0 1056 0.0378 0.9174 0.9569 0.9367 116 0.9671 0.9304 0.9484 158 0.9762 0.9919 0.9840 124 0.9549 0.9573 0.9561 0.9898
0.0567 12.0 1152 0.0370 0.8824 0.9052 0.8936 116 0.9375 0.9494 0.9434 158 0.9609 0.9919 0.9762 124 0.9287 0.9497 0.9391 0.9882
0.0546 13.0 1248 0.0360 0.9160 0.9397 0.9277 116 0.9487 0.9367 0.9427 158 0.9385 0.9839 0.9606 124 0.9358 0.9523 0.9440 0.9898
0.0504 14.0 1344 0.0360 0.925 0.9569 0.9407 116 0.9671 0.9304 0.9484 158 0.9609 0.9919 0.9762 124 0.9525 0.9573 0.9549 0.9907
0.0484 15.0 1440 0.0369 0.9167 0.9483 0.9322 116 0.9610 0.9367 0.9487 158 0.9685 0.9919 0.9801 124 0.9501 0.9573 0.9537 0.9901
0.0449 16.0 1536 0.0340 0.8852 0.9310 0.9076 116 0.9671 0.9304 0.9484 158 0.9683 0.9839 0.976 124 0.9425 0.9472 0.9449 0.9885
0.0432 17.0 1632 0.0353 0.9167 0.9483 0.9322 116 0.9608 0.9304 0.9453 158 0.984 0.9919 0.9880 124 0.9548 0.9548 0.9548 0.9901
0.0427 18.0 1728 0.0387 0.904 0.9741 0.9378 116 0.9597 0.9051 0.9316 158 0.984 0.9919 0.9880 124 0.9499 0.9523 0.9511 0.9885
0.0421 19.0 1824 0.0363 0.9561 0.9397 0.9478 116 0.9551 0.9430 0.9490 158 0.984 0.9919 0.9880 124 0.9646 0.9573 0.9609 0.9898
0.0363 20.0 1920 0.0379 0.9402 0.9483 0.9442 116 0.9375 0.9494 0.9434 158 0.984 0.9919 0.9880 124 0.9527 0.9623 0.9575 0.9893
0.0349 21.0 2016 0.0364 0.9167 0.9483 0.9322 116 0.9548 0.9367 0.9457 158 0.984 0.9919 0.9880 124 0.9525 0.9573 0.9549 0.9898
0.0373 22.0 2112 0.0324 0.9483 0.9483 0.9483 116 0.9494 0.9494 0.9494 158 0.984 0.9919 0.9880 124 0.9599 0.9623 0.9611 0.9918
0.0331 23.0 2208 0.0345 0.9310 0.9310 0.9310 116 0.9490 0.9430 0.9460 158 0.984 0.9919 0.9880 124 0.9548 0.9548 0.9548 0.9901
0.0317 24.0 2304 0.0406 0.925 0.9569 0.9407 116 0.9551 0.9430 0.9490 158 0.9762 0.9919 0.9840 124 0.9527 0.9623 0.9575 0.9890
0.0328 25.0 2400 0.0368 0.9322 0.9483 0.9402 116 0.9474 0.9114 0.9290 158 0.984 0.9919 0.9880 124 0.9544 0.9472 0.9508 0.9898
0.0299 26.0 2496 0.0364 0.9167 0.9483 0.9322 116 0.9545 0.9304 0.9423 158 0.984 0.9919 0.9880 124 0.9524 0.9548 0.9536 0.9907
0.0314 27.0 2592 0.0386 0.9483 0.9483 0.9483 116 0.9484 0.9304 0.9393 158 0.9609 0.9919 0.9762 124 0.9524 0.9548 0.9536 0.9907
0.0297 28.0 2688 0.0392 0.9160 0.9397 0.9277 116 0.9412 0.9114 0.9260 158 0.9762 0.9919 0.9840 124 0.9447 0.9447 0.9447 0.9887
0.0263 29.0 2784 0.0401 0.8810 0.9569 0.9174 116 0.9295 0.9177 0.9236 158 0.984 0.9919 0.9880 124 0.9312 0.9523 0.9416 0.9890
0.026 30.0 2880 0.0483 0.9316 0.9397 0.9356 116 0.9317 0.9494 0.9404 158 0.9762 0.9919 0.9840 124 0.9455 0.9598 0.9526 0.9887
0.0271 31.0 2976 0.0421 0.8934 0.9397 0.9160 116 0.9187 0.9304 0.9245 158 0.9762 0.9919 0.9840 124 0.9289 0.9523 0.9404 0.9874
0.0263 32.0 3072 0.0404 0.9153 0.9310 0.9231 116 0.9673 0.9367 0.9518 158 0.984 0.9919 0.9880 124 0.9571 0.9523 0.9547 0.9896
0.0255 33.0 3168 0.0429 0.9153 0.9310 0.9231 116 0.9542 0.9241 0.9389 158 0.984 0.9919 0.9880 124 0.9520 0.9472 0.9496 0.9896
0.0256 34.0 3264 0.0402 0.9397 0.9397 0.9397 116 0.9367 0.9367 0.9367 158 0.9762 0.9919 0.9840 124 0.95 0.9548 0.9524 0.9896
0.0202 35.0 3360 0.0407 0.9304 0.9224 0.9264 116 0.9375 0.9494 0.9434 158 0.9685 0.9919 0.9801 124 0.9453 0.9548 0.95 0.9904
0.0232 36.0 3456 0.0391 0.9167 0.9483 0.9322 116 0.9608 0.9304 0.9453 158 0.9762 0.9919 0.9840 124 0.9524 0.9548 0.9536 0.9898
0.0216 37.0 3552 0.0351 0.9153 0.9310 0.9231 116 0.9490 0.9430 0.9460 158 0.9762 0.9919 0.9840 124 0.9476 0.9548 0.9512 0.9898
0.0218 38.0 3648 0.0353 0.9304 0.9224 0.9264 116 0.9494 0.9494 0.9494 158 0.9762 0.9919 0.9840 124 0.9524 0.9548 0.9536 0.9909
0.0193 39.0 3744 0.0407 0.9237 0.9397 0.9316 116 0.9481 0.9241 0.9359 158 0.9762 0.9919 0.9840 124 0.9497 0.9497 0.9497 0.9904
0.0214 40.0 3840 0.0386 0.9483 0.9483 0.9483 116 0.9742 0.9557 0.9649 158 0.9685 0.9919 0.9801 124 0.9648 0.9648 0.9648 0.9918
0.0201 41.0 3936 0.0369 0.9237 0.9397 0.9316 116 0.9490 0.9430 0.9460 158 0.9685 0.9919 0.9801 124 0.9478 0.9573 0.9525 0.9901
0.0193 42.0 4032 0.0399 0.9322 0.9483 0.9402 116 0.9548 0.9367 0.9457 158 0.984 0.9919 0.9880 124 0.9573 0.9573 0.9573 0.9901
0.0198 43.0 4128 0.0393 0.9244 0.9483 0.9362 116 0.9675 0.9430 0.9551 158 0.984 0.9919 0.9880 124 0.9598 0.9598 0.9598 0.9915
0.0195 44.0 4224 0.0413 0.9076 0.9310 0.9191 116 0.9477 0.9177 0.9325 158 0.9762 0.9919 0.9840 124 0.9447 0.9447 0.9447 0.9896
0.0173 45.0 4320 0.0384 0.9244 0.9483 0.9362 116 0.9477 0.9177 0.9325 158 0.9762 0.9919 0.9840 124 0.9497 0.9497 0.9497 0.9898
0.0199 46.0 4416 0.0408 0.9016 0.9483 0.9244 116 0.9671 0.9304 0.9484 158 0.984 0.9919 0.9880 124 0.9524 0.9548 0.9536 0.9904
0.0183 47.0 4512 0.0361 0.9402 0.9483 0.9442 116 0.9554 0.9494 0.9524 158 0.9685 0.9919 0.9801 124 0.9551 0.9623 0.9587 0.9912
0.0194 48.0 4608 0.0444 0.9244 0.9483 0.9362 116 0.9548 0.9367 0.9457 158 0.984 0.9919 0.9880 124 0.9549 0.9573 0.9561 0.9893
0.0158 49.0 4704 0.0417 0.9237 0.9397 0.9316 116 0.9542 0.9241 0.9389 158 0.9685 0.9919 0.9801 124 0.9497 0.9497 0.9497 0.9898
0.0159 50.0 4800 0.0441 0.9322 0.9483 0.9402 116 0.9484 0.9304 0.9393 158 0.976 0.9839 0.9799 124 0.9523 0.9523 0.9523 0.9890
0.0147 51.0 4896 0.0449 0.9231 0.9310 0.9270 116 0.9304 0.9304 0.9304 158 0.9685 0.9919 0.9801 124 0.9403 0.9497 0.9450 0.9885
0.0161 52.0 4992 0.0544 0.9060 0.9138 0.9099 116 0.9669 0.9241 0.9450 158 0.9762 0.9919 0.9840 124 0.9518 0.9422 0.9470 0.9874
0.0157 53.0 5088 0.0422 0.9076 0.9310 0.9191 116 0.9419 0.9241 0.9329 158 0.9685 0.9919 0.9801 124 0.9401 0.9472 0.9437 0.9893
0.0163 54.0 5184 0.0470 0.9068 0.9224 0.9145 116 0.9367 0.9367 0.9367 158 0.9762 0.9919 0.9840 124 0.9403 0.9497 0.9450 0.9887
0.0158 55.0 5280 0.0436 0.9231 0.9310 0.9270 116 0.9125 0.9241 0.9182 158 0.9685 0.9919 0.9801 124 0.9332 0.9472 0.9401 0.9890
0.016 56.0 5376 0.0449 0.9237 0.9397 0.9316 116 0.9236 0.9177 0.9206 158 0.9762 0.9919 0.9840 124 0.9401 0.9472 0.9437 0.9887
0.0148 57.0 5472 0.0447 0.9316 0.9397 0.9356 116 0.9114 0.9114 0.9114 158 0.9685 0.9919 0.9801 124 0.9353 0.9447 0.94 0.9887
0.015 58.0 5568 0.0446 0.9237 0.9397 0.9316 116 0.9536 0.9114 0.9320 158 0.9762 0.9919 0.9840 124 0.9519 0.9447 0.9483 0.9898
0.0145 59.0 5664 0.0426 0.9402 0.9483 0.9442 116 0.9236 0.9177 0.9206 158 0.9762 0.9919 0.9840 124 0.945 0.9497 0.9474 0.9898
0.0142 60.0 5760 0.0441 0.9573 0.9655 0.9614 116 0.9423 0.9304 0.9363 158 0.984 0.9919 0.9880 124 0.9598 0.9598 0.9598 0.9912
0.0127 61.0 5856 0.0461 0.9487 0.9569 0.9528 116 0.9367 0.9367 0.9367 158 0.9685 0.9919 0.9801 124 0.9502 0.9598 0.9550 0.9909
0.0131 62.0 5952 0.0470 0.9316 0.9397 0.9356 116 0.9419 0.9241 0.9329 158 0.9685 0.9919 0.9801 124 0.9474 0.9497 0.9486 0.9896
0.0137 63.0 6048 0.0427 0.9322 0.9483 0.9402 116 0.9608 0.9304 0.9453 158 0.9762 0.9919 0.9840 124 0.9572 0.9548 0.9560 0.9912
0.0117 64.0 6144 0.0469 0.9561 0.9397 0.9478 116 0.9245 0.9304 0.9274 158 0.9683 0.9839 0.976 124 0.9474 0.9497 0.9486 0.9904
0.0131 65.0 6240 0.0437 0.9256 0.9655 0.9451 116 0.9226 0.9051 0.9137 158 0.9685 0.9919 0.9801 124 0.9380 0.9497 0.9438 0.9898
0.0132 66.0 6336 0.0435 0.9565 0.9483 0.9524 116 0.9412 0.9114 0.9260 158 0.9609 0.9919 0.9762 124 0.9520 0.9472 0.9496 0.9901
0.0117 67.0 6432 0.0413 0.9328 0.9569 0.9447 116 0.9172 0.9114 0.9143 158 0.9683 0.9839 0.976 124 0.9378 0.9472 0.9425 0.9898
0.0124 68.0 6528 0.0440 0.9328 0.9569 0.9447 116 0.9545 0.9304 0.9423 158 0.9685 0.9919 0.9801 124 0.9525 0.9573 0.9549 0.9907
0.0122 69.0 6624 0.0427 0.9558 0.9310 0.9432 116 0.9367 0.9367 0.9367 158 0.9685 0.9919 0.9801 124 0.9523 0.9523 0.9523 0.9907
0.0105 70.0 6720 0.0465 0.9153 0.9310 0.9231 116 0.9416 0.9177 0.9295 158 0.9683 0.9839 0.976 124 0.9422 0.9422 0.9422 0.9887
0.0115 71.0 6816 0.0467 0.9569 0.9569 0.9569 116 0.9539 0.9177 0.9355 158 0.9683 0.9839 0.976 124 0.9594 0.9497 0.9545 0.9904
0.01 72.0 6912 0.0480 0.9316 0.9397 0.9356 116 0.9542 0.9241 0.9389 158 0.9683 0.9839 0.976 124 0.9520 0.9472 0.9496 0.9907
0.0112 73.0 7008 0.0464 0.9322 0.9483 0.9402 116 0.9539 0.9177 0.9355 158 0.9683 0.9839 0.976 124 0.9520 0.9472 0.9496 0.9904
0.0104 74.0 7104 0.0475 0.9397 0.9397 0.9397 116 0.9673 0.9367 0.9518 158 0.9683 0.9839 0.976 124 0.9595 0.9523 0.9559 0.9904
0.0103 75.0 7200 0.0518 0.9167 0.9483 0.9322 116 0.9536 0.9114 0.9320 158 0.9683 0.9839 0.976 124 0.9471 0.9447 0.9459 0.9890
0.0106 76.0 7296 0.0484 0.9322 0.9483 0.9402 116 0.9539 0.9177 0.9355 158 0.9683 0.9839 0.976 124 0.9520 0.9472 0.9496 0.9901
0.0099 77.0 7392 0.0491 0.925 0.9569 0.9407 116 0.9470 0.9051 0.9256 158 0.9683 0.9839 0.976 124 0.9471 0.9447 0.9459 0.9893
0.0097 78.0 7488 0.0462 0.9244 0.9483 0.9362 116 0.9536 0.9114 0.9320 158 0.9683 0.9839 0.976 124 0.9495 0.9447 0.9471 0.9898
0.0086 79.0 7584 0.0451 0.9310 0.9310 0.9310 116 0.9419 0.9241 0.9329 158 0.9683 0.9839 0.976 124 0.9471 0.9447 0.9459 0.9901
0.0094 80.0 7680 0.0496 0.9231 0.9310 0.9270 116 0.9474 0.9114 0.9290 158 0.9683 0.9839 0.976 124 0.9468 0.9397 0.9433 0.9887
0.0079 81.0 7776 0.0452 0.9478 0.9397 0.9437 116 0.9542 0.9241 0.9389 158 0.9683 0.9839 0.976 124 0.9569 0.9472 0.9520 0.9901
0.0075 82.0 7872 0.0472 0.9478 0.9397 0.9437 116 0.9539 0.9177 0.9355 158 0.9683 0.9839 0.976 124 0.9567 0.9447 0.9507 0.9901
0.0083 83.0 7968 0.0510 0.9483 0.9483 0.9483 116 0.9412 0.9114 0.9260 158 0.9683 0.9839 0.976 124 0.9519 0.9447 0.9483 0.9898
0.0085 84.0 8064 0.0474 0.9244 0.9483 0.9362 116 0.9355 0.9177 0.9265 158 0.9683 0.9839 0.976 124 0.9425 0.9472 0.9449 0.9901
0.0085 85.0 8160 0.0480 0.9310 0.9310 0.9310 116 0.9419 0.9241 0.9329 158 0.9683 0.9839 0.976 124 0.9471 0.9447 0.9459 0.9898
0.0092 86.0 8256 0.0472 0.9316 0.9397 0.9356 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9495 0.9447 0.9471 0.9893
0.0083 87.0 8352 0.0464 0.9402 0.9483 0.9442 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9520 0.9472 0.9496 0.9904
0.0081 88.0 8448 0.0442 0.9328 0.9569 0.9447 116 0.9355 0.9177 0.9265 158 0.9683 0.9839 0.976 124 0.945 0.9497 0.9474 0.9909
0.0085 89.0 8544 0.0436 0.9237 0.9397 0.9316 116 0.9295 0.9177 0.9236 158 0.9683 0.9839 0.976 124 0.94 0.9447 0.9424 0.9904
0.0092 90.0 8640 0.0458 0.9412 0.9655 0.9532 116 0.9412 0.9114 0.9260 158 0.9683 0.9839 0.976 124 0.9497 0.9497 0.9497 0.9907
0.0087 91.0 8736 0.0473 0.9474 0.9310 0.9391 116 0.9416 0.9177 0.9295 158 0.9683 0.9839 0.976 124 0.9518 0.9422 0.9470 0.9896
0.0084 92.0 8832 0.0475 0.9397 0.9397 0.9397 116 0.9481 0.9241 0.9359 158 0.9683 0.9839 0.976 124 0.9520 0.9472 0.9496 0.9904
0.0087 93.0 8928 0.0472 0.9402 0.9483 0.9442 116 0.9351 0.9114 0.9231 158 0.9683 0.9839 0.976 124 0.9471 0.9447 0.9459 0.9901
0.008 94.0 9024 0.0460 0.9237 0.9397 0.9316 116 0.9355 0.9177 0.9265 158 0.9683 0.9839 0.976 124 0.9424 0.9447 0.9435 0.9901
0.0075 95.0 9120 0.0459 0.9322 0.9483 0.9402 116 0.9355 0.9177 0.9265 158 0.9683 0.9839 0.976 124 0.9449 0.9472 0.9460 0.9901
0.0088 96.0 9216 0.0472 0.9322 0.9483 0.9402 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9496 0.9472 0.9484 0.9898
0.0079 97.0 9312 0.0472 0.9237 0.9397 0.9316 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9471 0.9447 0.9459 0.9898
0.0075 98.0 9408 0.0479 0.9322 0.9483 0.9402 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9496 0.9472 0.9484 0.9901
0.0075 99.0 9504 0.0479 0.9316 0.9397 0.9356 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9495 0.9447 0.9471 0.9898
0.0079 100.0 9600 0.0479 0.9316 0.9397 0.9356 116 0.9477 0.9177 0.9325 158 0.9683 0.9839 0.976 124 0.9495 0.9447 0.9471 0.9898

Framework versions

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