flan-t5-large-summary

This model is a fine-tuned version of google/flan-t5-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3277
  • Rouge1: 69.554
  • Rouge2: 59.2044
  • Rougel: 67.6581
  • Rougelsum: 67.7174
  • Gen Len: 18.7309

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: 20

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 190 0.3832 67.2926 53.7031 64.7974 64.8071 18.8179
No log 2.0 380 0.3090 67.8051 55.3515 65.6548 65.6747 18.8232
0.2632 3.0 570 0.2876 68.3985 56.4896 66.3492 66.3648 18.7889
0.2632 4.0 760 0.2789 68.5676 56.4035 66.101 66.1396 18.8100
0.2632 5.0 950 0.2805 68.2045 56.6864 66.2411 66.3045 18.7784
0.2625 6.0 1140 0.2827 68.4741 57.1103 66.101 66.1991 18.7810
0.2625 7.0 1330 0.2767 68.9503 57.7255 66.8972 66.9236 18.7916
0.2048 8.0 1520 0.2776 69.1733 57.5766 66.7948 66.9347 18.7968
0.2048 9.0 1710 0.2777 69.7098 58.867 67.8471 67.8675 18.7388
0.2048 10.0 1900 0.2855 69.2753 57.8341 67.1037 67.2396 18.7757
0.1653 11.0 2090 0.2819 69.7836 58.5212 67.6087 67.6426 18.7916
0.1653 12.0 2280 0.2918 70.0288 59.2524 68.0356 68.0754 18.7573
0.1653 13.0 2470 0.2940 69.7288 59.2246 67.8426 67.8537 18.7704
0.1421 14.0 2660 0.2995 69.6257 58.8437 67.6509 67.6521 18.7810
0.1421 15.0 2850 0.3042 69.5083 58.6743 67.4254 67.5589 18.7625
0.1201 16.0 3040 0.3114 69.3398 58.9756 67.4566 67.5762 18.7810
0.1201 17.0 3230 0.3158 69.3569 58.8509 67.3013 67.4321 18.7520
0.1201 18.0 3420 0.3215 69.7484 59.1145 67.6617 67.6992 18.7573
0.1076 19.0 3610 0.3254 69.5556 59.2392 67.7187 67.7966 18.7520
0.1076 20.0 3800 0.3277 69.554 59.2044 67.6581 67.7174 18.7309

Framework versions

  • Transformers 4.43.2
  • Pytorch 2.2.0a0+81ea7a4
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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