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robbert_seed34_1311

This model is a fine-tuned version of pdelobelle/robbert-v2-dutch-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3777
  • Precisions: 0.8501
  • Recall: 0.8262
  • F-measure: 0.8370
  • Accuracy: 0.9450

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: 7.5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 34
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 14

Training results

Training Loss Epoch Step Validation Loss Precisions Recall F-measure Accuracy
0.4251 1.0 236 0.2557 0.7903 0.7339 0.7510 0.9248
0.2162 2.0 472 0.3018 0.8386 0.7336 0.7532 0.9200
0.1275 3.0 708 0.2461 0.8347 0.7758 0.7858 0.9364
0.0797 4.0 944 0.2773 0.8694 0.7843 0.8114 0.9383
0.049 5.0 1180 0.2767 0.8314 0.8143 0.8200 0.9419
0.03 6.0 1416 0.3036 0.8126 0.8106 0.8104 0.9407
0.0189 7.0 1652 0.3637 0.8051 0.8146 0.8073 0.9395
0.014 8.0 1888 0.3762 0.8479 0.7926 0.8135 0.9436
0.012 9.0 2124 0.3649 0.8486 0.8019 0.8205 0.9443
0.0045 10.0 2360 0.3966 0.8530 0.8000 0.8200 0.9431
0.0057 11.0 2596 0.3856 0.8564 0.8129 0.8307 0.9441
0.0054 12.0 2832 0.3777 0.8501 0.8262 0.8370 0.9450
0.0025 13.0 3068 0.3792 0.8608 0.8207 0.8369 0.9458
0.0019 14.0 3304 0.3859 0.8581 0.8149 0.8318 0.9455

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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