robbert_testrun / README.md
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metadata
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
  - generated_from_trainer
metrics:
  - recall
  - accuracy
model-index:
  - name: robbert_testrun
    results: []

robbert_testrun

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: 0.3318
  • Precisions: 0.8562
  • Recall: 0.8095
  • F-measure: 0.8293
  • Accuracy: 0.9476

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: 42
  • 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
0.4465 1.0 269 0.3166 0.8058 0.6865 0.6693 0.9046
0.2204 2.0 538 0.2474 0.8108 0.7990 0.7979 0.9295
0.133 3.0 807 0.2529 0.8072 0.7719 0.7830 0.9357
0.087 4.0 1076 0.2601 0.8462 0.7886 0.8012 0.9415
0.0578 5.0 1345 0.2896 0.8286 0.8106 0.8186 0.9418
0.0307 6.0 1614 0.3017 0.8474 0.8065 0.8240 0.9433
0.0257 7.0 1883 0.3435 0.8488 0.8129 0.8270 0.9407
0.0159 8.0 2152 0.3318 0.8562 0.8095 0.8293 0.9476
0.0086 9.0 2421 0.3629 0.8433 0.8065 0.8224 0.9451
0.0067 10.0 2690 0.3700 0.8648 0.8020 0.8272 0.9451
0.0064 11.0 2959 0.3835 0.8328 0.8108 0.8203 0.9425
0.0041 12.0 3228 0.3625 0.8454 0.8094 0.8255 0.9447
0.0028 13.0 3497 0.3734 0.8450 0.8097 0.8254 0.9451
0.0021 14.0 3766 0.3706 0.8469 0.8119 0.8274 0.9462

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1