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arabert_cross_organization_task7_fold1

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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_fold1
    results: []

arabert_cross_organization_task7_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: 1.0235
  • Qwk: 0.3186
  • Mse: 1.0235

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 4.5492 0.0033 4.5492
No log 0.2667 4 2.3313 0.0265 2.3313
No log 0.4 6 0.9380 0.1593 0.9380
No log 0.5333 8 0.7299 0.3211 0.7299
No log 0.6667 10 1.0765 0.2403 1.0765
No log 0.8 12 0.9948 0.2992 0.9948
No log 0.9333 14 0.7246 0.3691 0.7246
No log 1.0667 16 0.8317 0.3374 0.8317
No log 1.2 18 1.1310 0.2565 1.1310
No log 1.3333 20 0.8172 0.3590 0.8172
No log 1.4667 22 0.6362 0.4637 0.6362
No log 1.6 24 0.7141 0.4179 0.7141
No log 1.7333 26 0.8099 0.3916 0.8099
No log 1.8667 28 0.8171 0.3801 0.8171
No log 2.0 30 0.6256 0.4325 0.6256
No log 2.1333 32 0.6044 0.4368 0.6044
No log 2.2667 34 0.6559 0.4218 0.6559
No log 2.4 36 0.6944 0.4358 0.6944
No log 2.5333 38 0.8347 0.3992 0.8347
No log 2.6667 40 0.7015 0.4476 0.7015
No log 2.8 42 0.5980 0.4984 0.5980
No log 2.9333 44 0.6999 0.4162 0.6999
No log 3.0667 46 0.9852 0.3253 0.9852
No log 3.2 48 0.8781 0.3521 0.8781
No log 3.3333 50 0.6081 0.4705 0.6081
No log 3.4667 52 0.5650 0.5161 0.5650
No log 3.6 54 0.6909 0.4496 0.6909
No log 3.7333 56 0.9750 0.3479 0.9750
No log 3.8667 58 1.0120 0.3345 1.0120
No log 4.0 60 0.7745 0.3864 0.7745
No log 4.1333 62 0.5602 0.4789 0.5602
No log 4.2667 64 0.5317 0.5191 0.5317
No log 4.4 66 0.6043 0.4530 0.6043
No log 4.5333 68 0.9138 0.3450 0.9138
No log 4.6667 70 1.0543 0.2899 1.0543
No log 4.8 72 0.9173 0.3364 0.9173
No log 4.9333 74 0.6723 0.4180 0.6723
No log 5.0667 76 0.6232 0.4325 0.6232
No log 5.2 78 0.7547 0.3914 0.7547
No log 5.3333 80 0.9923 0.3422 0.9923
No log 5.4667 82 1.1410 0.3118 1.1410
No log 5.6 84 0.9779 0.3534 0.9779
No log 5.7333 86 0.8238 0.4080 0.8238
No log 5.8667 88 0.8201 0.4073 0.8201
No log 6.0 90 0.9149 0.3516 0.9149
No log 6.1333 92 1.0529 0.3263 1.0529
No log 6.2667 94 1.0383 0.3165 1.0383
No log 6.4 96 0.9200 0.3612 0.9200
No log 6.5333 98 0.8061 0.3776 0.8061
No log 6.6667 100 0.8442 0.3648 0.8442
No log 6.8 102 0.8632 0.3618 0.8632
No log 6.9333 104 0.8772 0.3675 0.8772
No log 7.0667 106 0.9942 0.3310 0.9942
No log 7.2 108 1.0411 0.3115 1.0411
No log 7.3333 110 0.9094 0.3720 0.9094
No log 7.4667 112 0.8811 0.3764 0.8811
No log 7.6 114 0.9874 0.3393 0.9874
No log 7.7333 116 1.1141 0.2953 1.1141
No log 7.8667 118 1.1732 0.2682 1.1732
No log 8.0 120 1.2079 0.2587 1.2079
No log 8.1333 122 1.1465 0.2875 1.1465
No log 8.2667 124 1.0235 0.3252 1.0235
No log 8.4 126 0.9569 0.3373 0.9569
No log 8.5333 128 0.9933 0.3246 0.9933
No log 8.6667 130 1.0961 0.2757 1.0961
No log 8.8 132 1.2178 0.2280 1.2178
No log 8.9333 134 1.2733 0.2266 1.2733
No log 9.0667 136 1.3165 0.2226 1.3165
No log 9.2 138 1.2781 0.2220 1.2781
No log 9.3333 140 1.2042 0.2320 1.2042
No log 9.4667 142 1.1543 0.2486 1.1543
No log 9.6 144 1.0986 0.2779 1.0986
No log 9.7333 146 1.0621 0.2914 1.0621
No log 9.8667 148 1.0338 0.3043 1.0338
No log 10.0 150 1.0235 0.3186 1.0235

Framework versions

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