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Arabic_FineTuningAraBERT_AugV4_k1_task1_organization_fold1

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metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: Arabic_FineTuningAraBERT_AugV4_k1_task1_organization_fold1
    results: []

Arabic_FineTuningAraBERT_AugV4_k1_task1_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: 0.7620
  • Qwk: 0.7042
  • Mse: 0.7620
  • Rmse: 0.8729

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 0.0714 2 3.6124 -0.0132 3.6124 1.9006
No log 0.1429 4 1.8035 0.0072 1.8035 1.3429
No log 0.2143 6 0.9159 0.1026 0.9159 0.9570
No log 0.2857 8 0.7706 0.3348 0.7706 0.8778
No log 0.3571 10 1.3346 0.2257 1.3346 1.1552
No log 0.4286 12 1.2293 0.2257 1.2293 1.1088
No log 0.5 14 0.8303 0.3951 0.8303 0.9112
No log 0.5714 16 0.7716 0.4425 0.7716 0.8784
No log 0.6429 18 0.6770 0.5333 0.6770 0.8228
No log 0.7143 20 0.6677 0.6182 0.6677 0.8171
No log 0.7857 22 0.5707 0.6231 0.5707 0.7554
No log 0.8571 24 0.5062 0.6733 0.5062 0.7115
No log 0.9286 26 0.5458 0.5508 0.5458 0.7388
No log 1.0 28 0.5303 0.6828 0.5303 0.7282
No log 1.0714 30 0.5012 0.6557 0.5012 0.7080
No log 1.1429 32 0.4980 0.6828 0.4980 0.7057
No log 1.2143 34 0.5893 0.6211 0.5893 0.7677
No log 1.2857 36 0.6739 0.6786 0.6739 0.8209
No log 1.3571 38 0.7754 0.6447 0.7754 0.8806
No log 1.4286 40 0.8049 0.6613 0.8049 0.8972
No log 1.5 42 0.8029 0.6120 0.8029 0.8961
No log 1.5714 44 0.7854 0.5779 0.7854 0.8862
No log 1.6429 46 0.7768 0.6396 0.7768 0.8813
No log 1.7143 48 0.7709 0.6486 0.7709 0.8780
No log 1.7857 50 0.7285 0.6160 0.7285 0.8535
No log 1.8571 52 0.5849 0.5294 0.5849 0.7648
No log 1.9286 54 0.5560 0.5164 0.5560 0.7456
No log 2.0 56 0.6040 0.5576 0.6040 0.7772
No log 2.0714 58 0.7966 0.5405 0.7966 0.8925
No log 2.1429 60 0.8970 0.5078 0.8970 0.9471
No log 2.2143 62 0.8134 0.5939 0.8134 0.9019
No log 2.2857 64 0.7359 0.6232 0.7359 0.8579
No log 2.3571 66 0.7887 0.3824 0.7887 0.8881
No log 2.4286 68 0.7449 0.4588 0.7449 0.8631
No log 2.5 70 0.7041 0.6453 0.7041 0.8391
No log 2.5714 72 0.8706 0.6769 0.8706 0.9331
No log 2.6429 74 1.0587 0.6957 1.0587 1.0289
No log 2.7143 76 0.9892 0.6488 0.9892 0.9946
No log 2.7857 78 0.7240 0.6744 0.7240 0.8509
No log 2.8571 80 0.4759 0.6364 0.4759 0.6898
No log 2.9286 82 0.5055 0.5157 0.5055 0.7110
No log 3.0 84 0.5233 0.5157 0.5233 0.7234
No log 3.0714 86 0.4751 0.5302 0.4751 0.6893
No log 3.1429 88 0.5147 0.6387 0.5147 0.7174
No log 3.2143 90 0.6567 0.7651 0.6567 0.8104
No log 3.2857 92 0.7222 0.6729 0.7222 0.8498
No log 3.3571 94 0.7476 0.6453 0.7476 0.8646
No log 3.4286 96 0.8091 0.6376 0.8091 0.8995
No log 3.5 98 0.8363 0.6453 0.8363 0.9145
No log 3.5714 100 0.8654 0.7042 0.8654 0.9302
No log 3.6429 102 0.8417 0.7042 0.8417 0.9174
No log 3.7143 104 0.7806 0.6872 0.7806 0.8835
No log 3.7857 106 0.7126 0.6453 0.7126 0.8442
No log 3.8571 108 0.7201 0.6453 0.7201 0.8486
No log 3.9286 110 0.7687 0.6872 0.7687 0.8768
No log 4.0 112 0.8380 0.7042 0.8380 0.9154
No log 4.0714 114 0.8143 0.6872 0.8143 0.9024
No log 4.1429 116 0.8054 0.7042 0.8054 0.8974
No log 4.2143 118 0.8669 0.6557 0.8669 0.9311
No log 4.2857 120 0.8679 0.6557 0.8679 0.9316
No log 4.3571 122 0.8411 0.7042 0.8411 0.9171
No log 4.4286 124 0.8101 0.6453 0.8101 0.9001
No log 4.5 126 0.8224 0.7614 0.8224 0.9068
No log 4.5714 128 0.8112 0.8119 0.8112 0.9007
No log 4.6429 130 0.7025 0.7614 0.7025 0.8381
No log 4.7143 132 0.5948 0.6872 0.5948 0.7712
No log 4.7857 134 0.5557 0.6571 0.5557 0.7454
No log 4.8571 136 0.5748 0.7042 0.5748 0.7581
No log 4.9286 138 0.6399 0.7799 0.6399 0.8000
No log 5.0 140 0.6768 0.6686 0.6768 0.8227
No log 5.0714 142 0.7147 0.7042 0.7147 0.8454
No log 5.1429 144 0.6956 0.6453 0.6956 0.8340
No log 5.2143 146 0.7307 0.6453 0.7307 0.8548
No log 5.2857 148 0.7958 0.6613 0.7958 0.8921
No log 5.3571 150 0.8007 0.6613 0.8007 0.8948
No log 5.4286 152 0.7583 0.6613 0.7583 0.8708
No log 5.5 154 0.6943 0.6453 0.6943 0.8333
No log 5.5714 156 0.6583 0.6429 0.6583 0.8113
No log 5.6429 158 0.6565 0.6613 0.6565 0.8102
No log 5.7143 160 0.7078 0.7284 0.7078 0.8413
No log 5.7857 162 0.7690 0.8121 0.7690 0.8769
No log 5.8571 164 0.7825 0.8121 0.7825 0.8846
No log 5.9286 166 0.7413 0.8121 0.7413 0.8610
No log 6.0 168 0.7217 0.7907 0.7217 0.8495
No log 6.0714 170 0.6900 0.7515 0.6900 0.8307
No log 6.1429 172 0.6854 0.6613 0.6854 0.8279
No log 6.2143 174 0.7411 0.6613 0.7411 0.8609
No log 6.2857 176 0.7943 0.7614 0.7943 0.8912
No log 6.3571 178 0.8542 0.7556 0.8542 0.9242
No log 6.4286 180 0.8404 0.7892 0.8404 0.9167
No log 6.5 182 0.8195 0.7393 0.8195 0.9052
No log 6.5714 184 0.7813 0.7154 0.7813 0.8839
No log 6.6429 186 0.7764 0.7154 0.7764 0.8812
No log 6.7143 188 0.7663 0.6429 0.7663 0.8754
No log 6.7857 190 0.7531 0.7154 0.7531 0.8678
No log 6.8571 192 0.7491 0.7154 0.7491 0.8655
No log 6.9286 194 0.7724 0.7393 0.7724 0.8788
No log 7.0 196 0.7571 0.7048 0.7571 0.8701
No log 7.0714 198 0.7078 0.7284 0.7078 0.8413
No log 7.1429 200 0.6651 0.7331 0.6651 0.8155
No log 7.2143 202 0.6309 0.7331 0.6309 0.7943
No log 7.2857 204 0.6506 0.7331 0.6506 0.8066
No log 7.3571 206 0.7157 0.7284 0.7157 0.8460
No log 7.4286 208 0.7367 0.7284 0.7367 0.8583
No log 7.5 210 0.7571 0.7614 0.7571 0.8701
No log 7.5714 212 0.7919 0.7042 0.7919 0.8899
No log 7.6429 214 0.8154 0.7042 0.8154 0.9030
No log 7.7143 216 0.8134 0.7042 0.8134 0.9019
No log 7.7857 218 0.7885 0.7042 0.7885 0.8880
No log 7.8571 220 0.7690 0.6872 0.7690 0.8769
No log 7.9286 222 0.7516 0.6872 0.7516 0.8670
No log 8.0 224 0.7383 0.6872 0.7383 0.8593
No log 8.0714 226 0.7214 0.6872 0.7214 0.8494
No log 8.1429 228 0.7246 0.6872 0.7246 0.8512
No log 8.2143 230 0.7395 0.6872 0.7395 0.8600
No log 8.2857 232 0.7649 0.6686 0.7649 0.8746
No log 8.3571 234 0.7811 0.6686 0.7811 0.8838
No log 8.4286 236 0.7939 0.7284 0.7939 0.8910
No log 8.5 238 0.7853 0.7799 0.7853 0.8862
No log 8.5714 240 0.7595 0.6686 0.7595 0.8715
No log 8.6429 242 0.7337 0.6686 0.7337 0.8566
No log 8.7143 244 0.7204 0.7042 0.7204 0.8487
No log 8.7857 246 0.7168 0.6872 0.7168 0.8466
No log 8.8571 248 0.7320 0.6872 0.7320 0.8556
No log 8.9286 250 0.7438 0.6872 0.7438 0.8624
No log 9.0 252 0.7619 0.6872 0.7619 0.8729
No log 9.0714 254 0.7843 0.7042 0.7843 0.8856
No log 9.1429 256 0.7976 0.7042 0.7976 0.8931
No log 9.2143 258 0.7966 0.7042 0.7966 0.8925
No log 9.2857 260 0.7947 0.7042 0.7947 0.8915
No log 9.3571 262 0.7958 0.7042 0.7958 0.8921
No log 9.4286 264 0.7946 0.7042 0.7946 0.8914
No log 9.5 266 0.7873 0.7042 0.7873 0.8873
No log 9.5714 268 0.7777 0.7042 0.7777 0.8819
No log 9.6429 270 0.7712 0.7042 0.7712 0.8782
No log 9.7143 272 0.7660 0.7042 0.7660 0.8752
No log 9.7857 274 0.7634 0.7042 0.7634 0.8737
No log 9.8571 276 0.7619 0.7042 0.7619 0.8729
No log 9.9286 278 0.7619 0.7042 0.7619 0.8729
No log 10.0 280 0.7620 0.7042 0.7620 0.8729

Framework versions

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