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Hub-Repoop-1706130115

This model is a fine-tuned version of Kevinger/setfit-hub-report on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1746
  • F1: 0.7727
  • Roc Auc: 0.8666
  • Accuracy: 0.7637

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 13

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
No log 1.0 277 0.3104 0.0 0.5 0.0
0.3599 2.0 554 0.2312 0.5624 0.7027 0.4135
0.3599 3.0 831 0.1897 0.7479 0.8275 0.6730
0.2035 4.0 1108 0.1768 0.7645 0.8546 0.7363
0.2035 5.0 1385 0.1760 0.7649 0.8579 0.7447
0.1422 6.0 1662 0.1788 0.7559 0.8562 0.7447
0.1422 7.0 1939 0.1766 0.7633 0.8617 0.7553
0.1096 8.0 2216 0.1746 0.7727 0.8666 0.7637
0.1096 9.0 2493 0.1891 0.7457 0.8511 0.7363
0.0891 10.0 2770 0.1855 0.7524 0.8540 0.7405
0.0769 11.0 3047 0.1824 0.7655 0.8629 0.7574
0.0769 12.0 3324 0.1835 0.7655 0.8629 0.7532
0.0706 13.0 3601 0.1867 0.7604 0.8603 0.7511

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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Model size
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Tensor type
F32
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