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robbert_seed36_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: 0.3538
  • Precisions: 0.8351
  • Recall: 0.8079
  • F-measure: 0.8173
  • Accuracy: 0.9422

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: 36
  • 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
0.4364 1.0 236 0.2547 0.8525 0.7285 0.7372 0.9231
0.2196 2.0 472 0.2772 0.8456 0.7521 0.7718 0.9291
0.1273 3.0 708 0.2681 0.8056 0.7798 0.7897 0.9315
0.0799 4.0 944 0.2971 0.8835 0.7898 0.8158 0.9393
0.0541 5.0 1180 0.3302 0.8515 0.7815 0.8016 0.9373
0.0358 6.0 1416 0.3291 0.8140 0.7901 0.7994 0.9385
0.0217 7.0 1652 0.3538 0.8351 0.8079 0.8173 0.9422
0.0145 8.0 1888 0.3622 0.8331 0.8000 0.8113 0.9431
0.0092 9.0 2124 0.3782 0.8190 0.8098 0.8116 0.9402
0.0091 10.0 2360 0.4023 0.8499 0.7967 0.8149 0.9422
0.0068 11.0 2596 0.3932 0.8293 0.8062 0.8154 0.9409
0.0053 12.0 2832 0.3894 0.8415 0.7942 0.8108 0.9412
0.0023 13.0 3068 0.3910 0.8379 0.7987 0.8127 0.9426
0.0035 14.0 3304 0.3919 0.8349 0.7990 0.8110 0.9422

Framework versions

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