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test-dialogue-summarization

This model is a fine-tuned version of google/flan-t5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3647
  • Rouge1: 43.7125
  • Rouge2: 20.8696
  • Rougel: 20.4726
  • Rougelsum: 20.4726
  • Gen Len: 15.005

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: 7
  • eval_batch_size: 7
  • 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 Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.9658 1.0 186 2.6549 47.8375 19.6224 19.3309 19.3309 15.65
2.8292 2.0 372 2.5659 46.3424 19.6335 20.017 20.017 14.965
2.7598 3.0 558 2.5190 45.6451 19.7504 20.0363 20.0363 15.07
2.6531 4.0 744 2.4796 45.0646 19.649 19.6929 19.6929 14.9
2.5946 5.0 930 2.4526 44.0678 19.4902 20.0463 20.0463 15.01
2.5868 6.0 1116 2.4340 44.7027 19.7504 20.0391 20.0391 14.765
2.5896 7.0 1302 2.4179 44.5941 19.8653 20.0073 20.0073 14.745
2.5626 8.0 1488 2.3981 44.6259 19.9902 20.3022 20.3022 15.1
2.4633 9.0 1674 2.3921 44.6047 20.4376 20.3104 20.3104 14.97
2.5217 10.0 1860 2.3826 44.2188 19.9486 20.3353 20.3353 14.995
2.48 11.0 2046 2.3766 44.4635 20.6357 20.3618 20.3618 14.99
2.4502 12.0 2232 2.3723 44.0093 20.7614 20.3647 20.3647 14.995
2.4946 13.0 2418 2.3677 43.8165 20.947 20.4526 20.4526 15.035
2.4372 14.0 2604 2.3651 44.0221 20.9248 20.5763 20.5763 14.92
2.4606 15.0 2790 2.3647 43.7125 20.8696 20.4726 20.4726 15.005

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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