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reward-bert-duplicate-answer-2

This model is a fine-tuned version of klue/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4506
  • Accuracy: 0.0

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: 9e-05
  • train_batch_size: 6
  • eval_batch_size: 6
  • seed: 2023
  • gradient_accumulation_steps: 10
  • total_train_batch_size: 60
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7099 0.26 100 0.6931 1.0
0.6983 0.53 200 0.6912 0.0
0.4911 0.79 300 0.4506 0.0

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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