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pogny-1-128-test

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: 1.6910
  • Accuracy: 0.4376
  • F1: 0.2665

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: 0.01
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
2.1835 1.0 603 1.6910 0.4376 0.2665

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.2.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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