generated_from_trainer

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IndoBert-base-ler

This model is a fine-tuned version of indobenchmark/indobert-base-p1 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 Overall Precision Overall Recall Overall F1 Overall Accuracy Jenis amar F1 Jenis dakwaan F1 Jenis perkara F1 Melanggar uu (dakwaan) F1 Melanggar uu (pertimbangan hukum) F1 Melanggar uu (tuntutan) F1 Nama hakim anggota F1 Nama hakim ketua F1 Nama jaksa F1 Nama panitera F1 Nama pengacara F1 Nama pengadilan F1 Nama saksi F1 Nama terdakwa F1 Nomor putusan F1 Putusan hukuman F1 Tanggal kejadian F1 Tanggal putusan F1 Tingkat kasus F1 Tuntutan hukuman F1
0.0214 1.0 7322 0.0174 0.7920 0.7699 0.7808 0.9956 0.8514 0.6352 0.6728 0.5940 0.5044 0.7329 0.8602 0.7357 0.8160 0.8355 0.6585 0.9661 0.8130 0.8053 0.9248 0.5354 0.3278 0.9372 0.9173 0.7353
0.0127 2.0 14644 0.0162 0.7760 0.7960 0.7859 0.9955 0.8982 0.6809 0.7038 0.5598 0.4747 0.6963 0.8733 0.8681 0.8604 0.8858 0.7114 0.9803 0.7601 0.8242 0.9318 0.6187 0.3976 0.9351 0.9560 0.7015
0.0117 3.0 21966 0.0172 0.7830 0.7701 0.7765 0.9953 0.8487 0.6657 0.7051 0.5092 0.5336 0.7518 0.8460 0.8093 0.7043 0.6803 0.7242 0.9802 0.8191 0.8039 0.9346 0.5290 0.3797 0.9312 0.9564 0.7534
0.0088 4.0 29288 0.0175 0.8086 0.8019 0.8052 0.9960 0.9093 0.7876 0.7571 0.6362 0.5500 0.7384 0.8832 0.8440 0.7949 0.8913 0.6986 0.9874 0.8193 0.8378 0.9089 0.5590 0.3968 0.9534 0.9640 0.7724
0.0092 5.0 36610 0.0171 0.8070 0.8035 0.8053 0.9958 0.8686 0.6188 0.7521 0.5808 0.5625 0.7645 0.8825 0.8168 0.8656 0.8557 0.7155 0.9803 0.8242 0.8132 0.9323 0.6011 0.3756 0.9211 0.9653 0.7570
0.0057 6.0 43932 0.0184 0.8157 0.8077 0.8117 0.9958 0.9050 0.8299 0.7505 0.6424 0.4908 0.7571 0.8822 0.8740 0.8625 0.8970 0.7475 0.9802 0.8158 0.8327 0.9389 0.5801 0.3892 0.944 0.9635 0.8073
0.0057 7.0 51254 0.0203 0.7988 0.8277 0.8130 0.9959 0.9273 0.7900 0.7673 0.5932 0.5577 0.7811 0.8863 0.8553 0.8743 0.8945 0.7176 0.9681 0.8316 0.8231 0.9374 0.5983 0.4006 0.9110 0.9620 0.8203
0.0054 8.0 58576 0.0209 0.8263 0.8058 0.8159 0.9959 0.8996 0.8097 0.7661 0.6445 0.5613 0.7778 0.9079 0.7732 0.8783 0.8968 0.7080 0.9910 0.8227 0.8355 0.9401 0.5395 0.3542 0.9279 0.9706 0.7937
0.003 9.0 65898 0.0244 0.8255 0.8096 0.8175 0.9956 0.9277 0.7944 0.7146 0.6556 0.5502 0.7842 0.8564 0.8798 0.8813 0.8955 0.7547 0.9857 0.8221 0.8270 0.9399 0.6681 0.3873 0.9468 0.9654 0.7912
0.0031 10.0 73220 0.0256 0.8297 0.8206 0.8251 0.9959 0.9103 0.8239 0.7598 0.6639 0.5665 0.7609 0.9008 0.8765 0.8867 0.9002 0.7590 0.9982 0.8359 0.8322 0.9409 0.5965 0.3774 0.9402 0.9635 0.8070
0.0021 11.0 80542 0.0259 0.8365 0.8238 0.8301 0.9960 0.9191 0.8383 0.7966 0.6644 0.5874 0.7530 0.8944 0.8675 0.8878 0.9041 0.7500 0.9964 0.8319 0.8307 0.9332 0.6536 0.3909 0.9316 0.9670 0.8496
0.0015 12.0 87864 0.0267 0.8344 0.8204 0.8273 0.9960 0.9270 0.8141 0.7881 0.6816 0.5730 0.7855 0.8964 0.8745 0.8926 0.8913 0.7805 0.9946 0.8291 0.8275 0.9332 0.6376 0.3753 0.9273 0.9761 0.8035
0.001 13.0 95186 0.0297 0.8316 0.8201 0.8258 0.9960 0.9339 0.8373 0.7351 0.6392 0.5955 0.7816 0.9022 0.8763 0.8968 0.8861 0.7826 0.9964 0.8408 0.8296 0.9223 0.6689 0.3906 0.9404 0.9762 0.8070
0.0007 14.0 102508 0.0317 0.8299 0.8211 0.8254 0.9959 0.9387 0.8462 0.7520 0.6820 0.5964 0.7791 0.9010 0.8770 0.8932 0.9039 0.8142 0.9964 0.8325 0.8262 0.9171 0.6637 0.3807 0.9316 0.9799 0.8450
0.0003 15.0 109830 0.0334 0.8340 0.8274 0.8307 0.9960 0.9368 0.8222 0.7744 0.6737 0.5977 0.7877 0.9053 0.8817 0.8745 0.9038 0.8083 0.9964 0.8345 0.8335 0.9311 0.6681 0.3793 0.9406 0.9762 0.8436
0.0001 16.0 117152 0.0348 0.8392 0.8292 0.8342 0.9961 0.9381 0.8202 0.7895 0.6704 0.5885 0.7783 0.9045 0.8854 0.8905 0.9056 0.8288 0.9964 0.8385 0.8264 0.9359 0.6659 0.3870 0.9430 0.9817 0.8348

Framework versions