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final_bart

This model is a fine-tuned version of gogamza/kobart-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.6848
  • Rouge1: 35.7722
  • Rouge2: 12.5127
  • Rougel: 23.3002
  • Rdass: 0.6248
  • Bleu1: 30.5261
  • Bleu2: 17.6264
  • Bleu3: 10.3974
  • Bleu4: 5.4348
  • Gen Len: 53.47

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: 3e-05
  • train_batch_size: 64
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5.0

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rdass Bleu1 Bleu2 Bleu3 Bleu4 Gen Len
2.1542 1.5 1000 2.7491 33.5554 11.2371 22.006 0.6093 27.9938 15.5354 8.2494 4.42 50.08
2.0071 2.99 2000 2.6813 35.0501 12.2759 22.6669 0.6155 29.6866 17.1396 9.7016 5.3559 54.04
1.8694 4.49 3000 2.6848 35.7722 12.5127 23.3002 0.6248 30.5261 17.6264 10.3974 5.4348 53.47

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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