Arabic_FineTuningAraBERT_AugV5_k5_task3_organization_fold1

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9938
  • Qwk: -0.0820
  • Mse: 0.9938
  • Rmse: 0.9969

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Qwk Mse Rmse
No log 0.0769 2 6.4882 0.0120 6.4882 2.5472
No log 0.1538 4 2.8615 0.0763 2.8615 1.6916
No log 0.2308 6 1.2489 0.0 1.2489 1.1175
No log 0.3077 8 1.2975 0.0120 1.2975 1.1391
No log 0.3846 10 1.4121 0.0253 1.4121 1.1883
No log 0.4615 12 1.0061 0.0253 1.0061 1.0030
No log 0.5385 14 0.7697 0.1879 0.7697 0.8773
No log 0.6154 16 1.3628 0.0 1.3628 1.1674
No log 0.6923 18 1.3278 0.0 1.3278 1.1523
No log 0.7692 20 1.0906 0.0 1.0906 1.0443
No log 0.8462 22 0.9415 0.0 0.9415 0.9703
No log 0.9231 24 0.8609 0.0763 0.8609 0.9278
No log 1.0 26 1.0114 0.0120 1.0114 1.0057
No log 1.0769 28 0.8698 0.0120 0.8698 0.9326
No log 1.1538 30 1.0945 -0.1139 1.0945 1.0462
No log 1.2308 32 1.5711 0.0 1.5711 1.2534
No log 1.3077 34 1.4726 0.0 1.4726 1.2135
No log 1.3846 36 1.3741 0.0120 1.3741 1.1722
No log 1.4615 38 1.3272 -0.1139 1.3272 1.1521
No log 1.5385 40 0.8637 -0.4602 0.8637 0.9293
No log 1.6154 42 0.7004 0.0 0.7004 0.8369
No log 1.6923 44 0.7366 0.0 0.7366 0.8583
No log 1.7692 46 0.9411 -0.4275 0.9411 0.9701
No log 1.8462 48 1.3252 0.0120 1.3252 1.1512
No log 1.9231 50 1.5053 0.0 1.5053 1.2269
No log 2.0 52 1.5209 0.0 1.5209 1.2332
No log 2.0769 54 1.3356 0.0 1.3356 1.1557
No log 2.1538 56 0.9869 0.0 0.9869 0.9934
No log 2.2308 58 0.8408 0.1646 0.8408 0.9170
No log 2.3077 60 0.8580 0.0 0.8580 0.9263
No log 2.3846 62 0.9236 0.0 0.9236 0.9611
No log 2.4615 64 0.9641 0.0120 0.9641 0.9819
No log 2.5385 66 0.9209 -0.1139 0.9209 0.9596
No log 2.6154 68 0.8825 -0.4426 0.8825 0.9394
No log 2.6923 70 0.8844 -0.2692 0.8844 0.9404
No log 2.7692 72 0.7791 -0.2791 0.7791 0.8827
No log 2.8462 74 0.7874 -0.2791 0.7874 0.8873
No log 2.9231 76 0.9282 -0.2791 0.9282 0.9634
No log 3.0 78 1.2708 -0.4275 1.2708 1.1273
No log 3.0769 80 1.2567 -0.4426 1.2567 1.1210
No log 3.1538 82 0.8678 -0.2791 0.8678 0.9316
No log 3.2308 84 0.5034 0.4211 0.5034 0.7095
No log 3.3077 86 0.4776 0.4590 0.4776 0.6911
No log 3.3846 88 0.5597 0.2443 0.5597 0.7481
No log 3.4615 90 0.9531 0.1239 0.9531 0.9763
No log 3.5385 92 1.4142 -0.2222 1.4142 1.1892
No log 3.6154 94 1.4356 -0.1058 1.4356 1.1982
No log 3.6923 96 1.1902 -0.1074 1.1902 1.0909
No log 3.7692 98 0.8565 0.1239 0.8565 0.9255
No log 3.8462 100 0.5664 0.1239 0.5664 0.7526
No log 3.9231 102 0.4910 0.4211 0.4910 0.7007
No log 4.0 104 0.6272 -0.2791 0.6272 0.7920
No log 4.0769 106 0.8063 -0.2692 0.8063 0.8979
No log 4.1538 108 0.9651 -0.2692 0.9651 0.9824
No log 4.2308 110 1.1817 -0.2595 1.1817 1.0871
No log 4.3077 112 1.2166 -0.2571 1.2166 1.1030
No log 4.3846 114 1.0163 -0.4602 1.0163 1.0081
No log 4.4615 116 0.9236 -0.2692 0.9236 0.9611
No log 4.5385 118 0.9074 -0.2692 0.9074 0.9526
No log 4.6154 120 0.8761 -0.2692 0.8761 0.9360
No log 4.6923 122 0.9739 -0.2595 0.9739 0.9869
No log 4.7692 124 1.0063 -0.2571 1.0063 1.0032
No log 4.8462 126 1.0867 0.0403 1.0867 1.0425
No log 4.9231 128 1.0136 0.0403 1.0136 1.0068
No log 5.0 130 0.9020 0.2443 0.9020 0.9497
No log 5.0769 132 0.8408 0.2443 0.8408 0.9170
No log 5.1538 134 1.0709 0.0403 1.0709 1.0348
No log 5.2308 136 1.1822 0.0403 1.1822 1.0873
No log 5.3077 138 0.9413 0.0571 0.9413 0.9702
No log 5.3846 140 0.7544 0.1270 0.7544 0.8686
No log 5.4615 142 0.7863 0.2443 0.7863 0.8867
No log 5.5385 144 1.1251 0.0403 1.1251 1.0607
No log 5.6154 146 1.2707 0.0403 1.2707 1.1273
No log 5.6923 148 1.1481 0.0403 1.1481 1.0715
No log 5.7692 150 1.1328 0.0403 1.1328 1.0644
No log 5.8462 152 1.2027 0.0403 1.2027 1.0967
No log 5.9231 154 1.2689 0.0403 1.2689 1.1265
No log 6.0 156 1.2094 0.0403 1.2094 1.0997
No log 6.0769 158 0.9554 0.0403 0.9554 0.9774
No log 6.1538 160 0.7977 0.2443 0.7977 0.8932
No log 6.2308 162 0.8738 0.0403 0.8738 0.9348
No log 6.3077 164 0.9806 0.0403 0.9806 0.9903
No log 6.3846 166 0.9343 0.0403 0.9343 0.9666
No log 6.4615 168 0.9511 0.0403 0.9511 0.9753
No log 6.5385 170 1.0951 0.0403 1.0951 1.0465
No log 6.6154 172 1.2844 0.0403 1.2844 1.1333
No log 6.6923 174 1.1801 0.0403 1.1801 1.0863
No log 6.7692 176 0.9290 0.2443 0.9290 0.9638
No log 6.8462 178 0.8739 -0.0820 0.8739 0.9348
No log 6.9231 180 0.9441 -0.0820 0.9441 0.9716
No log 7.0 182 1.1352 0.0571 1.1352 1.0655
No log 7.0769 184 1.2470 0.0403 1.2470 1.1167
No log 7.1538 186 1.1198 -0.2595 1.1198 1.0582
No log 7.2308 188 0.9832 -0.0820 0.9832 0.9916
No log 7.3077 190 0.8924 -0.2692 0.8924 0.9447
No log 7.3846 192 0.9152 -0.2692 0.9152 0.9566
No log 7.4615 194 1.0180 -0.0708 1.0180 1.0090
No log 7.5385 196 1.1520 -0.2595 1.1520 1.0733
No log 7.6154 198 1.1170 -0.2595 1.1170 1.0569
No log 7.6923 200 1.0034 -0.0708 1.0034 1.0017
No log 7.7692 202 0.9057 -0.0708 0.9057 0.9517
No log 7.8462 204 0.9190 -0.0708 0.9190 0.9587
No log 7.9231 206 0.9038 -0.0708 0.9038 0.9507
No log 8.0 208 0.8591 -0.0708 0.8591 0.9269
No log 8.0769 210 0.8657 -0.0820 0.8657 0.9304
No log 8.1538 212 0.9487 -0.0820 0.9487 0.9740
No log 8.2308 214 1.0921 0.0403 1.0921 1.0450
No log 8.3077 216 1.1481 0.0403 1.1481 1.0715
No log 8.3846 218 1.0795 0.0403 1.0795 1.0390
No log 8.4615 220 0.9810 -0.0820 0.9810 0.9905
No log 8.5385 222 0.8751 -0.0820 0.8751 0.9355
No log 8.6154 224 0.8409 -0.0820 0.8409 0.9170
No log 8.6923 226 0.8786 -0.0820 0.8786 0.9373
No log 8.7692 228 0.9480 -0.0820 0.9480 0.9736
No log 8.8462 230 1.0155 -0.0820 1.0155 1.0077
No log 8.9231 232 1.0158 -0.0820 1.0158 1.0079
No log 9.0 234 1.0166 -0.0820 1.0166 1.0083
No log 9.0769 236 1.0048 -0.0820 1.0048 1.0024
No log 9.1538 238 1.0121 -0.0820 1.0121 1.0060
No log 9.2308 240 1.0128 -0.0820 1.0128 1.0064
No log 9.3077 242 1.0097 -0.0820 1.0097 1.0048
No log 9.3846 244 1.0094 -0.0820 1.0094 1.0047
No log 9.4615 246 1.0006 -0.0820 1.0006 1.0003
No log 9.5385 248 1.0092 -0.0820 1.0092 1.0046
No log 9.6154 250 1.0080 -0.0820 1.0080 1.0040
No log 9.6923 252 1.0038 -0.0820 1.0038 1.0019
No log 9.7692 254 0.9971 -0.0820 0.9971 0.9985
No log 9.8462 256 0.9948 -0.0820 0.9948 0.9974
No log 9.9231 258 0.9944 -0.0820 0.9944 0.9972
No log 10.0 260 0.9938 -0.0820 0.9938 0.9969

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu118
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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