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arabert_cross_organization_task6_fold3

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bert
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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_cross_organization_task6_fold3
    results: []

arabert_cross_organization_task6_fold3

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: 1.3563
  • Qwk: -0.0016
  • Mse: 1.3563

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: 64
  • eval_batch_size: 64
  • 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
No log 0.1111 2 5.0067 -0.0021 5.0067
No log 0.2222 4 2.3688 0.0294 2.3688
No log 0.3333 6 1.3423 -0.0120 1.3423
No log 0.4444 8 1.5207 -0.0996 1.5207
No log 0.5556 10 1.1292 -0.0620 1.1292
No log 0.6667 12 1.1093 -0.0624 1.1093
No log 0.7778 14 1.1280 -0.1037 1.1280
No log 0.8889 16 1.1271 -0.0458 1.1271
No log 1.0 18 1.1353 -0.0286 1.1353
No log 1.1111 20 1.2273 0.0 1.2273
No log 1.2222 22 1.1922 0.0071 1.1922
No log 1.3333 24 1.1874 0.0071 1.1874
No log 1.4444 26 1.1668 -0.0325 1.1668
No log 1.5556 28 1.1666 -0.0039 1.1666
No log 1.6667 30 1.1595 -0.0073 1.1595
No log 1.7778 32 1.1718 0.0290 1.1718
No log 1.8889 34 1.2238 0.0 1.2238
No log 2.0 36 1.2276 0.0 1.2276
No log 2.1111 38 1.1870 -0.0366 1.1870
No log 2.2222 40 1.1871 -0.0785 1.1871
No log 2.3333 42 1.2823 -0.0775 1.2823
No log 2.4444 44 1.2667 -0.0775 1.2667
No log 2.5556 46 1.1897 -0.1036 1.1897
No log 2.6667 48 1.2024 -0.0005 1.2024
No log 2.7778 50 1.2359 -0.0107 1.2359
No log 2.8889 52 1.2436 -0.0073 1.2436
No log 3.0 54 1.2335 -0.0335 1.2335
No log 3.1111 56 1.2366 -0.0073 1.2366
No log 3.2222 58 1.2111 -0.0305 1.2111
No log 3.3333 60 1.1935 0.0372 1.1935
No log 3.4444 62 1.2135 -0.0513 1.2135
No log 3.5556 64 1.2077 -0.0335 1.2077
No log 3.6667 66 1.2202 0.0152 1.2202
No log 3.7778 68 1.2293 0.0152 1.2293
No log 3.8889 70 1.2441 0.0021 1.2441
No log 4.0 72 1.2616 0.0583 1.2616
No log 4.1111 74 1.2524 -0.0046 1.2524
No log 4.2222 76 1.2555 -0.0433 1.2555
No log 4.3333 78 1.2534 0.0522 1.2534
No log 4.4444 80 1.2663 0.0174 1.2663
No log 4.5556 82 1.2903 -0.0521 1.2903
No log 4.6667 84 1.2865 -0.0521 1.2865
No log 4.7778 86 1.2537 -0.0389 1.2537
No log 4.8889 88 1.2394 -0.0348 1.2394
No log 5.0 90 1.2581 -0.0668 1.2581
No log 5.1111 92 1.2785 -0.0442 1.2785
No log 5.2222 94 1.2996 0.0353 1.2996
No log 5.3333 96 1.3274 0.0118 1.3274
No log 5.4444 98 1.3336 -0.0386 1.3336
No log 5.5556 100 1.2963 -0.0161 1.2963
No log 5.6667 102 1.2938 0.0144 1.2938
No log 5.7778 104 1.3454 -0.0160 1.3454
No log 5.8889 106 1.3525 -0.0233 1.3525
No log 6.0 108 1.3385 0.0349 1.3385
No log 6.1111 110 1.3741 -0.0338 1.3741
No log 6.2222 112 1.4104 -0.0362 1.4104
No log 6.3333 114 1.4214 -0.0478 1.4214
No log 6.4444 116 1.4394 -0.0301 1.4394
No log 6.5556 118 1.4439 -0.0301 1.4439
No log 6.6667 120 1.3931 -0.0486 1.3931
No log 6.7778 122 1.3303 -0.0123 1.3303
No log 6.8889 124 1.2675 -0.0795 1.2675
No log 7.0 126 1.2466 -0.0580 1.2466
No log 7.1111 128 1.2543 -0.0097 1.2543
No log 7.2222 130 1.2895 -0.0149 1.2895
No log 7.3333 132 1.3307 0.0443 1.3307
No log 7.4444 134 1.3809 -0.0384 1.3809
No log 7.5556 136 1.4319 -0.1211 1.4319
No log 7.6667 138 1.4611 -0.0542 1.4611
No log 7.7778 140 1.4378 -0.0509 1.4378
No log 7.8889 142 1.3913 -0.0200 1.3913
No log 8.0 144 1.3657 -0.0247 1.3657
No log 8.1111 146 1.3785 -0.0093 1.3785
No log 8.2222 148 1.3631 0.0143 1.3631
No log 8.3333 150 1.3158 -0.0532 1.3158
No log 8.4444 152 1.2825 0.0371 1.2825
No log 8.5556 154 1.2704 0.0035 1.2704
No log 8.6667 156 1.2773 0.0377 1.2773
No log 8.7778 158 1.2959 0.0377 1.2959
No log 8.8889 160 1.3175 0.0625 1.3175
No log 9.0 162 1.3404 -0.0274 1.3404
No log 9.1111 164 1.3572 -0.0400 1.3572
No log 9.2222 166 1.3639 -0.0274 1.3639
No log 9.3333 168 1.3672 -0.0274 1.3672
No log 9.4444 170 1.3652 -0.0274 1.3652
No log 9.5556 172 1.3654 -0.0146 1.3654
No log 9.6667 174 1.3609 -0.0016 1.3609
No log 9.7778 176 1.3588 -0.0016 1.3588
No log 9.8889 178 1.3572 -0.0016 1.3572
No log 10.0 180 1.3563 -0.0016 1.3563

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1