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arabert_cross_organization_task6_fold5

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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_fold5
    results: []

arabert_cross_organization_task6_fold5

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: 0.4946
  • Qwk: 0.7585
  • Mse: 0.4958

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 0.125 2 1.3569 0.2073 1.3566
No log 0.25 4 0.8917 0.3804 0.8926
No log 0.375 6 1.3940 0.5002 1.3954
No log 0.5 8 1.1581 0.5869 1.1599
No log 0.625 10 0.8359 0.5005 0.8373
No log 0.75 12 0.8352 0.6240 0.8368
No log 0.875 14 0.7817 0.6808 0.7831
No log 1.0 16 0.6321 0.7284 0.6335
No log 1.125 18 0.5497 0.7013 0.5509
No log 1.25 20 0.6330 0.7733 0.6344
No log 1.375 22 0.9312 0.7286 0.9326
No log 1.5 24 0.9410 0.7373 0.9424
No log 1.625 26 0.6704 0.7704 0.6717
No log 1.75 28 0.5140 0.6654 0.5150
No log 1.875 30 0.5258 0.6207 0.5266
No log 2.0 32 0.4993 0.7208 0.5003
No log 2.125 34 0.5995 0.7661 0.6008
No log 2.25 36 0.6850 0.7821 0.6865
No log 2.375 38 0.6445 0.7839 0.6460
No log 2.5 40 0.5426 0.7571 0.5438
No log 2.625 42 0.5374 0.7584 0.5385
No log 2.75 44 0.5401 0.7508 0.5413
No log 2.875 46 0.5560 0.7716 0.5572
No log 3.0 48 0.5460 0.7794 0.5472
No log 3.125 50 0.5399 0.7800 0.5410
No log 3.25 52 0.4966 0.7520 0.4976
No log 3.375 54 0.4783 0.7484 0.4792
No log 3.5 56 0.5055 0.7654 0.5064
No log 3.625 58 0.4947 0.7569 0.4955
No log 3.75 60 0.5387 0.7681 0.5397
No log 3.875 62 0.6614 0.8077 0.6627
No log 4.0 64 0.6356 0.8243 0.6369
No log 4.125 66 0.4951 0.7545 0.4959
No log 4.25 68 0.4581 0.7123 0.4588
No log 4.375 70 0.4776 0.7450 0.4784
No log 4.5 72 0.5531 0.7823 0.5543
No log 4.625 74 0.5792 0.8103 0.5805
No log 4.75 76 0.5337 0.7801 0.5349
No log 4.875 78 0.4762 0.7597 0.4771
No log 5.0 80 0.4679 0.7390 0.4687
No log 5.125 82 0.4753 0.7488 0.4762
No log 5.25 84 0.5131 0.7689 0.5143
No log 5.375 86 0.5442 0.7925 0.5455
No log 5.5 88 0.5074 0.7624 0.5086
No log 5.625 90 0.4586 0.7435 0.4596
No log 5.75 92 0.4498 0.7269 0.4507
No log 5.875 94 0.4604 0.7354 0.4614
No log 6.0 96 0.5055 0.7753 0.5068
No log 6.125 98 0.5761 0.7991 0.5776
No log 6.25 100 0.5566 0.7942 0.5580
No log 6.375 102 0.5097 0.7509 0.5109
No log 6.5 104 0.4777 0.7454 0.4787
No log 6.625 106 0.4691 0.7225 0.4700
No log 6.75 108 0.4712 0.7283 0.4720
No log 6.875 110 0.4817 0.7509 0.4827
No log 7.0 112 0.4772 0.7454 0.4781
No log 7.125 114 0.4790 0.7490 0.4799
No log 7.25 116 0.5003 0.7688 0.5014
No log 7.375 118 0.5353 0.7753 0.5366
No log 7.5 120 0.5284 0.7670 0.5297
No log 7.625 122 0.5075 0.7556 0.5086
No log 7.75 124 0.4824 0.7527 0.4834
No log 7.875 126 0.4782 0.7527 0.4792
No log 8.0 128 0.4745 0.7554 0.4755
No log 8.125 130 0.4803 0.7523 0.4813
No log 8.25 132 0.4946 0.7614 0.4957
No log 8.375 134 0.4938 0.7558 0.4950
No log 8.5 136 0.4888 0.7558 0.4900
No log 8.625 138 0.4775 0.7507 0.4786
No log 8.75 140 0.4714 0.7474 0.4724
No log 8.875 142 0.4668 0.7410 0.4677
No log 9.0 144 0.4672 0.7382 0.4681
No log 9.125 146 0.4689 0.7433 0.4698
No log 9.25 148 0.4738 0.7571 0.4748
No log 9.375 150 0.4814 0.7511 0.4825
No log 9.5 152 0.4866 0.7567 0.4877
No log 9.625 154 0.4900 0.7585 0.4911
No log 9.75 156 0.4909 0.7585 0.4921
No log 9.875 158 0.4930 0.7585 0.4942
No log 10.0 160 0.4946 0.7585 0.4958

Framework versions

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