fine-tuned-bart-20-epochs-wang-lab

This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1462
  • Rouge1: 0.2876
  • Rouge2: 0.1104
  • Rougel: 0.2587
  • Rougelsum: 0.2583
  • Gen Len: 15.32

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: 0.0001
  • train_batch_size: 4
  • eval_batch_size: 4
  • 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: 20

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 301 0.8236 0.2393 0.0872 0.2103 0.2098 15.1
2.6644 2.0 602 0.7800 0.2486 0.0882 0.219 0.2187 14.24
2.6644 3.0 903 0.7623 0.3152 0.131 0.2914 0.2901 15.83
0.6713 4.0 1204 0.7802 0.2909 0.104 0.2577 0.2577 14.4
0.4641 5.0 1505 0.8159 0.2986 0.1058 0.2629 0.2606 14.71
0.4641 6.0 1806 0.8451 0.3212 0.1374 0.2892 0.2892 15.3
0.2986 7.0 2107 0.8913 0.2965 0.115 0.2724 0.2728 15.25
0.2986 8.0 2408 0.9194 0.2686 0.1036 0.2395 0.2389 15.07
0.2025 9.0 2709 0.9674 0.283 0.1077 0.2549 0.2535 15.38
0.1397 10.0 3010 0.9848 0.2805 0.1127 0.2484 0.2475 15.99
0.1397 11.0 3311 1.0356 0.2943 0.1158 0.2568 0.2586 15.32
0.0922 12.0 3612 1.0481 0.3291 0.1211 0.297 0.2999 15.39
0.0922 13.0 3913 1.0846 0.2861 0.1074 0.2473 0.2482 15.04
0.0618 14.0 4214 1.0941 0.2929 0.103 0.2511 0.2505 15.34
0.042 15.0 4515 1.1076 0.2639 0.1111 0.2349 0.2328 15.11
0.042 16.0 4816 1.1180 0.2825 0.1125 0.2465 0.2452 15.08
0.03 17.0 5117 1.1310 0.2924 0.1073 0.2527 0.2528 15.47
0.03 18.0 5418 1.1407 0.2823 0.1017 0.2491 0.2471 15.1
0.0204 19.0 5719 1.1445 0.2952 0.1142 0.2635 0.264 15.13
0.0153 20.0 6020 1.1462 0.2876 0.1104 0.2587 0.2583 15.32

Framework versions

  • Transformers 4.36.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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