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kuglerk_adapted_bert-base-cased

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8087

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: 4e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss
2.4035 1.0 84 2.1206
2.1438 2.0 168 1.9904
2.0971 3.0 252 2.0585
1.9539 4.0 336 1.9030
1.9094 5.0 420 1.8884
1.73 6.0 504 1.8904
1.7158 7.0 588 1.8781
1.5977 8.0 672 1.8708
1.5389 9.0 756 1.8401
1.5116 10.0 840 1.8857
1.4251 11.0 924 1.9454
1.4667 12.0 1008 1.8755
1.3729 13.0 1092 1.8515
1.2514 14.0 1176 1.8990
1.2987 15.0 1260 1.8410
1.1944 16.0 1344 1.8475
1.2191 17.0 1428 1.9417
1.1865 18.0 1512 1.9362
1.2222 19.0 1596 1.9161
1.1874 20.0 1680 1.9455
1.1469 21.0 1764 1.9746
1.0914 22.0 1848 1.8935
1.0565 23.0 1932 1.9497
1.123 24.0 2016 1.8756
1.1232 25.0 2100 1.9511

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.3
  • Tokenizers 0.13.3
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