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arabert_cross_organization_task7_fold0

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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_task7_fold0
    results: []

arabert_cross_organization_task7_fold0

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: 0.7058
  • Qwk: 0.5975
  • Mse: 0.7057

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 0.1333 2 3.8864 0.0541 3.8830
No log 0.2667 4 2.5481 0.0079 2.5460
No log 0.4 6 1.6996 0.2037 1.6983
No log 0.5333 8 1.3776 0.2939 1.3765
No log 0.6667 10 1.3355 0.3347 1.3345
No log 0.8 12 1.2773 0.3590 1.2767
No log 0.9333 14 1.4284 0.3342 1.4277
No log 1.0667 16 1.1577 0.3897 1.1573
No log 1.2 18 0.9645 0.4536 0.9641
No log 1.3333 20 1.1001 0.4324 1.0996
No log 1.4667 22 1.0995 0.4399 1.0990
No log 1.6 24 0.9787 0.4704 0.9783
No log 1.7333 26 0.8116 0.5438 0.8112
No log 1.8667 28 0.8107 0.5471 0.8103
No log 2.0 30 0.9069 0.4983 0.9063
No log 2.1333 32 0.8730 0.5346 0.8726
No log 2.2667 34 0.9141 0.5284 0.9138
No log 2.4 36 0.7576 0.6068 0.7578
No log 2.5333 38 0.7560 0.6087 0.7563
No log 2.6667 40 0.8005 0.6059 0.8007
No log 2.8 42 0.9430 0.5399 0.9430
No log 2.9333 44 0.8990 0.5542 0.8990
No log 3.0667 46 0.8494 0.5672 0.8494
No log 3.2 48 0.8095 0.5752 0.8094
No log 3.3333 50 0.7424 0.6012 0.7425
No log 3.4667 52 0.7009 0.6100 0.7011
No log 3.6 54 0.7078 0.6055 0.7080
No log 3.7333 56 0.8222 0.5652 0.8223
No log 3.8667 58 0.8211 0.5742 0.8212
No log 4.0 60 0.7561 0.5870 0.7562
No log 4.1333 62 0.6981 0.6055 0.6982
No log 4.2667 64 0.6970 0.6051 0.6971
No log 4.4 66 0.7327 0.5991 0.7326
No log 4.5333 68 0.8809 0.5424 0.8806
No log 4.6667 70 0.8266 0.5559 0.8263
No log 4.8 72 0.7118 0.5954 0.7117
No log 4.9333 74 0.6923 0.6040 0.6923
No log 5.0667 76 0.7259 0.5893 0.7259
No log 5.2 78 0.7425 0.5832 0.7425
No log 5.3333 80 0.6843 0.6051 0.6843
No log 5.4667 82 0.6647 0.6118 0.6647
No log 5.6 84 0.6805 0.6104 0.6804
No log 5.7333 86 0.7021 0.5992 0.7019
No log 5.8667 88 0.6896 0.6158 0.6894
No log 6.0 90 0.6658 0.6204 0.6657
No log 6.1333 92 0.6774 0.6118 0.6774
No log 6.2667 94 0.7472 0.5748 0.7471
No log 6.4 96 0.8444 0.5491 0.8442
No log 6.5333 98 0.8227 0.5502 0.8225
No log 6.6667 100 0.7455 0.5671 0.7453
No log 6.8 102 0.7062 0.5907 0.7060
No log 6.9333 104 0.6458 0.6143 0.6457
No log 7.0667 106 0.6289 0.6250 0.6288
No log 7.2 108 0.6373 0.6205 0.6371
No log 7.3333 110 0.6669 0.6113 0.6666
No log 7.4667 112 0.7012 0.6035 0.7009
No log 7.6 114 0.6942 0.5999 0.6939
No log 7.7333 116 0.6669 0.6083 0.6668
No log 7.8667 118 0.6470 0.6177 0.6469
No log 8.0 120 0.6439 0.6292 0.6438
No log 8.1333 122 0.6501 0.6098 0.6500
No log 8.2667 124 0.6801 0.6013 0.6800
No log 8.4 126 0.7382 0.5951 0.7380
No log 8.5333 128 0.7558 0.5885 0.7556
No log 8.6667 130 0.7227 0.5947 0.7225
No log 8.8 132 0.6780 0.6014 0.6780
No log 8.9333 134 0.6554 0.6101 0.6554
No log 9.0667 136 0.6520 0.6154 0.6520
No log 9.2 138 0.6597 0.6100 0.6596
No log 9.3333 140 0.6690 0.6141 0.6689
No log 9.4667 142 0.6790 0.6041 0.6789
No log 9.6 144 0.6910 0.5976 0.6909
No log 9.7333 146 0.7025 0.5975 0.7024
No log 9.8667 148 0.7059 0.5975 0.7057
No log 10.0 150 0.7058 0.5975 0.7057

Framework versions

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