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flan-t5-base-dialogsum_v2

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9323
  • Rouge1: 49.6194
  • Rouge2: 23.9441
  • Rougel: 47.1784
  • Rougelsum: 47.7351
  • Gen Len: 19.0

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.8419 1.0 1558 0.9686 49.1717 21.6321 46.5027 46.9099 19.0
0.7931 2.0 3116 0.9393 49.0429 25.016 46.8583 47.1894 19.0
0.7931 3.0 4674 0.9555 49.969 24.7039 47.6287 48.1426 19.0
0.7572 4.0 6232 0.9746 49.1309 23.2537 46.4771 46.9249 19.0
0.7417 5.0 7790 0.9820 49.2093 23.1137 46.6788 47.1939 19.0
0.7491 6.0 9348 0.9592 50.4655 25.5968 48.0925 48.6231 19.0
0.7181 7.0 10906 0.9593 50.6565 24.5502 48.0572 48.5985 19.0
0.7144 8.0 12464 0.9386 50.9351 25.9342 48.4183 48.898 19.0
0.7137 9.0 14022 0.9486 49.5404 23.7464 46.9305 47.4827 19.0
0.6728 10.0 15580 0.9419 49.9498 23.8617 47.3421 47.9081 19.0
0.6783 11.0 17138 0.9459 50.52 25.9799 48.0356 48.596 19.0
0.6708 12.0 18696 0.9552 49.85 23.8992 47.3564 47.8535 19.0
0.6515 13.0 20254 0.9462 49.7239 25.468 47.4924 48.0146 19.0
0.6419 14.0 21812 0.9507 49.8791 25.3529 47.5795 48.0845 19.0
0.6297 15.0 23370 0.9323 49.6194 23.9441 47.1784 47.7351 19.0
0.6354 16.0 24928 0.9408 50.3383 25.6301 48.1241 48.6641 19.0
0.6178 17.0 26486 0.9420 49.5266 24.6134 47.1452 47.6481 19.0
0.608 18.0 28044 0.9549 49.7907 24.9381 47.4622 48.0312 19.0
0.6205 19.0 29602 0.9580 49.687 25.1737 47.4014 47.8466 19.0
0.5946 20.0 31160 0.9519 50.1159 25.3671 47.8232 48.3411 19.0
0.6107 21.0 32718 0.9549 49.9508 24.746 47.5774 48.1047 19.0
0.591 22.0 34276 0.9543 50.1561 25.3451 47.8341 48.3492 19.0
0.6017 23.0 35834 0.9570 49.893 25.1383 47.503 48.059 19.0
0.5942 24.0 37392 0.9584 49.9479 24.9422 47.5917 48.1012 19.0
0.5826 25.0 38950 0.9592 49.9049 25.1102 47.5736 48.1165 19.0

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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