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robbert_seed37_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: 0.3848
  • Precisions: 0.8521
  • Recall: 0.8198
  • F-measure: 0.8327
  • Accuracy: 0.9441

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: 37
  • 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
0.4569 1.0 236 0.2571 0.7110 0.7130 0.7092 0.9217
0.222 2.0 472 0.2286 0.7904 0.7574 0.7685 0.9313
0.1311 3.0 708 0.2412 0.8047 0.7810 0.7875 0.9359
0.0813 4.0 944 0.2755 0.8019 0.7775 0.7886 0.9354
0.0552 5.0 1180 0.3120 0.8499 0.7793 0.8032 0.9409
0.0323 6.0 1416 0.3536 0.8350 0.7955 0.8099 0.9402
0.0212 7.0 1652 0.3789 0.8448 0.7817 0.8092 0.9405
0.0154 8.0 1888 0.3835 0.8419 0.7780 0.7971 0.9385
0.0119 9.0 2124 0.3906 0.8583 0.7812 0.8058 0.9388
0.0081 10.0 2360 0.3910 0.8477 0.7874 0.8062 0.9424
0.0052 11.0 2596 0.3839 0.8642 0.8087 0.8298 0.9431
0.0046 12.0 2832 0.3848 0.8521 0.8198 0.8327 0.9441
0.0018 13.0 3068 0.4017 0.8450 0.8125 0.8240 0.9438
0.0014 14.0 3304 0.4060 0.8571 0.8088 0.8265 0.9441

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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F32
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