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Hub-Repoop-1706132005

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: 0.1718
  • F1: 0.7750
  • Roc Auc: 0.8654
  • Accuracy: 0.7595

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 0.3053 0.0 0.5 0.0
0.3561 2.0 554 0.2275 0.5792 0.7105 0.4283
0.3561 3.0 831 0.1904 0.7453 0.8270 0.6730
0.2037 4.0 1108 0.1791 0.7602 0.8498 0.7257
0.2037 5.0 1385 0.1724 0.7614 0.8556 0.7405
0.144 6.0 1662 0.1733 0.7557 0.8546 0.7405
0.144 7.0 1939 0.1718 0.7750 0.8654 0.7595
0.1093 8.0 2216 0.1805 0.7605 0.8579 0.7468
0.1093 9.0 2493 0.1842 0.7484 0.8508 0.7342
0.0872 10.0 2770 0.1817 0.7597 0.8577 0.7447
0.0748 11.0 3047 0.1824 0.7561 0.8579 0.7468
0.0748 12.0 3324 0.1826 0.7663 0.8630 0.7553
0.0674 13.0 3601 0.1844 0.7594 0.8585 0.7489

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
109M params
Tensor type
F32
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