ec_classfication_0502_google_electra_base_discriminator

This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8369
  • F1: 0.8511

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: 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: 15

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 59 0.6505 0.3934
No log 2.0 118 0.4319 0.8211
No log 3.0 177 0.4704 0.8269
No log 4.0 236 0.4700 0.8571
No log 5.0 295 0.5886 0.8478
No log 6.0 354 0.8250 0.8
No log 7.0 413 0.6282 0.8571
No log 8.0 472 0.6684 0.8632
0.2241 9.0 531 0.7479 0.8632
0.2241 10.0 590 0.8523 0.8387
0.2241 11.0 649 0.7993 0.8511
0.2241 12.0 708 0.8075 0.8602
0.2241 13.0 767 0.8326 0.8511
0.2241 14.0 826 0.8350 0.8511
0.2241 15.0 885 0.8369 0.8511

Framework versions

  • Transformers 4.27.3
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.2
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