pogny-32-0.00002-fin

This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6989
  • Accuracy: 0.7527
  • F1: 0.7499

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.7236 1.0 2492 0.6820 0.7426 0.7392
0.5931 2.0 4984 0.6645 0.7520 0.7475
0.4497 3.0 7476 0.6989 0.7527 0.7499

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0a0+b5021ba
  • Datasets 2.6.2
  • Tokenizers 0.14.1
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