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arabert_cross_vocabulary_task5_fold0

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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_cross_vocabulary_task4_fold6
    results: []

arabert_cross_vocabulary_task4_fold6

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: 0.3809
  • Qwk: 0.7212
  • Mse: 0.3803

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Qwk Mse
No log 0.0290 2 3.5915 0.0135 3.5774
No log 0.0580 4 1.6728 0.1066 1.6543
No log 0.0870 6 0.9207 0.3071 0.9146
No log 0.1159 8 0.9451 0.4183 0.9392
No log 0.1449 10 1.0092 0.4761 1.0019
No log 0.1739 12 0.8467 0.4077 0.8353
No log 0.2029 14 0.7589 0.4123 0.7471
No log 0.2319 16 0.6332 0.4728 0.6243
No log 0.2609 18 0.6097 0.5641 0.6051
No log 0.2899 20 0.5389 0.5141 0.5354
No log 0.3188 22 0.5073 0.5047 0.5034
No log 0.3478 24 0.4996 0.5613 0.4954
No log 0.3768 26 0.4724 0.5931 0.4689
No log 0.4058 28 0.4067 0.6836 0.4044
No log 0.4348 30 0.4385 0.8033 0.4374
No log 0.4638 32 0.4624 0.8118 0.4616
No log 0.4928 34 0.4385 0.7922 0.4378
No log 0.5217 36 0.4184 0.6922 0.4169
No log 0.5507 38 0.4874 0.6033 0.4851
No log 0.5797 40 0.6206 0.5584 0.6172
No log 0.6087 42 0.7056 0.5187 0.7018
No log 0.6377 44 0.6335 0.5490 0.6305
No log 0.6667 46 0.4625 0.6195 0.4610
No log 0.6957 48 0.3971 0.7571 0.3968
No log 0.7246 50 0.4158 0.7849 0.4158
No log 0.7536 52 0.4127 0.7821 0.4127
No log 0.7826 54 0.4163 0.7855 0.4162
No log 0.8116 56 0.4055 0.7826 0.4053
No log 0.8406 58 0.3891 0.7730 0.3888
No log 0.8696 60 0.3833 0.7639 0.3829
No log 0.8986 62 0.3800 0.7588 0.3795
No log 0.9275 64 0.3788 0.7357 0.3783
No log 0.9565 66 0.3800 0.7299 0.3795
No log 0.9855 68 0.3809 0.7212 0.3803

Framework versions

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