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bart-base-paraphrasing
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: 0.6617
- Rouge1: 57.7088
- Rouge2: 51.0096
- Rougel: 54.7514
- Rougelsum: 56.3943
- Gen Len: 20.0
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: 4e-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 | 0.2 | 10 | 0.5263 | 58.2676 | 51.5842 | 55.5057 | 57.1584 | 19.94 |
No log | 0.4 | 20 | 0.5050 | 56.1604 | 48.7383 | 54.0373 | 55.372 | 20.0 |
No log | 0.6 | 30 | 0.4674 | 58.0617 | 51.4993 | 56.0368 | 56.9665 | 20.0 |
No log | 0.8 | 40 | 0.4545 | 57.5375 | 51.0203 | 55.5247 | 56.5761 | 19.94 |
No log | 1.0 | 50 | 0.4373 | 57.7263 | 50.8021 | 55.0549 | 56.35 | 19.98 |
No log | 1.2 | 60 | 0.4313 | 57.87 | 50.9904 | 54.9727 | 56.5379 | 19.97 |
No log | 1.4 | 70 | 0.4855 | 56.5101 | 49.3124 | 54.1572 | 55.0671 | 20.0 |
No log | 1.6 | 80 | 0.4202 | 56.6535 | 50.0302 | 53.6891 | 55.1016 | 19.96 |
No log | 1.8 | 90 | 0.4544 | 57.315 | 50.6289 | 54.642 | 55.7326 | 19.95 |
0.5858 | 2.0 | 100 | 0.4157 | 56.4569 | 48.8105 | 53.937 | 55.3515 | 20.0 |
0.5858 | 2.2 | 110 | 0.4555 | 57.8424 | 51.5966 | 55.6655 | 56.6862 | 20.0 |
0.5858 | 2.4 | 120 | 0.4196 | 58.2562 | 51.7596 | 55.5085 | 57.1823 | 19.97 |
0.5858 | 2.6 | 130 | 0.4334 | 58.6906 | 51.6106 | 55.6631 | 57.5254 | 19.89 |
0.5858 | 2.8 | 140 | 0.4710 | 56.5401 | 49.33 | 53.8792 | 55.0282 | 20.0 |
0.5858 | 3.0 | 150 | 0.4357 | 58.2083 | 52.0049 | 55.9938 | 57.1928 | 20.0 |
0.5858 | 3.2 | 160 | 0.4735 | 58.8112 | 52.2196 | 56.5004 | 57.7703 | 19.94 |
0.5858 | 3.4 | 170 | 0.4428 | 57.6778 | 50.6377 | 54.8752 | 56.4778 | 20.0 |
0.5858 | 3.6 | 180 | 0.4983 | 57.4124 | 50.4244 | 54.6163 | 56.0992 | 20.0 |
0.5858 | 3.8 | 190 | 0.4620 | 58.0701 | 51.5021 | 55.7222 | 56.8737 | 20.0 |
0.2865 | 4.0 | 200 | 0.4502 | 59.1191 | 52.7516 | 56.4389 | 57.7153 | 20.0 |
0.2865 | 4.2 | 210 | 0.4805 | 58.9064 | 52.7148 | 56.1058 | 57.6709 | 20.0 |
0.2865 | 4.4 | 220 | 0.4755 | 58.6883 | 52.1464 | 55.9164 | 57.3825 | 20.0 |
0.2865 | 4.6 | 230 | 0.4524 | 58.9916 | 52.1101 | 56.4116 | 57.9468 | 19.9 |
0.2865 | 4.8 | 240 | 0.4726 | 58.9953 | 52.8173 | 56.5846 | 58.0805 | 20.0 |
0.2865 | 5.0 | 250 | 0.4841 | 58.1058 | 51.614 | 55.3374 | 56.7617 | 20.0 |
0.2865 | 5.2 | 260 | 0.5047 | 58.2785 | 51.1874 | 55.5336 | 56.8795 | 20.0 |
0.2865 | 5.4 | 270 | 0.4658 | 57.2753 | 49.6038 | 53.9588 | 55.6038 | 19.91 |
0.2865 | 5.6 | 280 | 0.5261 | 58.1691 | 51.5254 | 55.2685 | 56.7787 | 20.0 |
0.2865 | 5.8 | 290 | 0.4833 | 57.8088 | 51.2838 | 54.8739 | 56.4374 | 20.0 |
0.1668 | 6.0 | 300 | 0.5067 | 58.2021 | 51.3629 | 55.3548 | 56.9093 | 19.99 |
0.1668 | 6.2 | 310 | 0.5461 | 58.0327 | 51.4051 | 55.3426 | 56.7923 | 20.0 |
0.1668 | 6.4 | 320 | 0.5463 | 58.1027 | 51.3706 | 55.1733 | 56.7923 | 19.9 |
0.1668 | 6.6 | 330 | 0.5837 | 57.6284 | 50.8245 | 54.6253 | 56.2127 | 20.0 |
0.1668 | 6.8 | 340 | 0.5221 | 58.0869 | 51.5448 | 55.4226 | 56.7532 | 20.0 |
0.1668 | 7.0 | 350 | 0.5433 | 58.7676 | 52.0403 | 56.2634 | 57.6441 | 20.0 |
0.1668 | 7.2 | 360 | 0.5498 | 57.9172 | 50.9727 | 55.1006 | 56.6018 | 20.0 |
0.1668 | 7.4 | 370 | 0.5581 | 57.4669 | 50.698 | 54.6448 | 56.1325 | 20.0 |
0.1668 | 7.6 | 380 | 0.5526 | 57.0821 | 50.298 | 54.1635 | 55.8059 | 20.0 |
0.1668 | 7.8 | 390 | 0.5548 | 57.5422 | 50.2734 | 54.2446 | 56.1223 | 20.0 |
0.1071 | 8.0 | 400 | 0.5620 | 57.4548 | 50.2657 | 54.5094 | 55.9422 | 20.0 |
0.1071 | 8.2 | 410 | 0.5772 | 57.4144 | 50.2443 | 54.5173 | 55.9331 | 20.0 |
0.1071 | 8.4 | 420 | 0.5857 | 57.2975 | 50.2116 | 54.5918 | 55.9931 | 20.0 |
0.1071 | 8.6 | 430 | 0.5827 | 58.4767 | 51.4318 | 55.4792 | 57.1284 | 20.0 |
0.1071 | 8.8 | 440 | 0.5728 | 58.4414 | 51.3523 | 55.2838 | 57.202 | 20.0 |
0.1071 | 9.0 | 450 | 0.5919 | 58.0499 | 51.3783 | 55.0748 | 56.6939 | 20.0 |
0.1071 | 9.2 | 460 | 0.5937 | 57.7604 | 50.845 | 54.8941 | 56.351 | 20.0 |
0.1071 | 9.4 | 470 | 0.5970 | 57.3655 | 50.4126 | 54.4522 | 55.7815 | 20.0 |
0.1071 | 9.6 | 480 | 0.5911 | 58.203 | 51.0367 | 55.3215 | 56.8485 | 20.0 |
0.1071 | 9.8 | 490 | 0.6121 | 58.2898 | 51.2749 | 55.4292 | 57.0241 | 20.0 |
0.0718 | 10.0 | 500 | 0.5903 | 58.2487 | 51.3838 | 55.4237 | 56.8863 | 20.0 |
0.0718 | 10.2 | 510 | 0.5983 | 58.2681 | 51.0925 | 55.2887 | 56.9562 | 20.0 |
0.0718 | 10.4 | 520 | 0.6308 | 57.9797 | 50.7386 | 54.995 | 56.5939 | 20.0 |
0.0718 | 10.6 | 530 | 0.6307 | 57.6269 | 50.5515 | 54.446 | 56.1544 | 20.0 |
0.0718 | 10.8 | 540 | 0.6173 | 57.9545 | 51.1005 | 54.9406 | 56.5732 | 20.0 |
0.0718 | 11.0 | 550 | 0.6322 | 58.3718 | 51.4321 | 55.4241 | 57.1879 | 20.0 |
0.0718 | 11.2 | 560 | 0.6027 | 58.6581 | 51.8607 | 55.6436 | 57.32 | 20.0 |
0.0718 | 11.4 | 570 | 0.6140 | 58.6476 | 51.7822 | 55.5845 | 57.3018 | 20.0 |
0.0718 | 11.6 | 580 | 0.6184 | 59.2454 | 52.4204 | 56.2174 | 57.9278 | 20.0 |
0.0718 | 11.8 | 590 | 0.6281 | 59.2945 | 52.8165 | 56.547 | 58.0674 | 20.0 |
0.0512 | 12.0 | 600 | 0.6128 | 58.2165 | 51.3689 | 55.37 | 56.8342 | 20.0 |
0.0512 | 12.2 | 610 | 0.6482 | 57.9196 | 50.9793 | 55.0883 | 56.6986 | 20.0 |
0.0512 | 12.4 | 620 | 0.6267 | 57.4782 | 50.1118 | 54.2802 | 55.8872 | 20.0 |
0.0512 | 12.6 | 630 | 0.6198 | 57.457 | 50.4079 | 54.2449 | 55.8118 | 20.0 |
0.0512 | 12.8 | 640 | 0.6500 | 57.6903 | 51.0627 | 55.0743 | 56.3025 | 20.0 |
0.0512 | 13.0 | 650 | 0.6265 | 57.4394 | 50.9013 | 54.7936 | 56.1688 | 20.0 |
0.0512 | 13.2 | 660 | 0.6817 | 58.4345 | 51.7087 | 55.291 | 57.0057 | 20.0 |
0.0512 | 13.4 | 670 | 0.6322 | 57.869 | 50.9503 | 54.8937 | 56.5178 | 20.0 |
0.0512 | 13.6 | 680 | 0.6424 | 57.8285 | 51.1014 | 55.0072 | 56.5022 | 20.0 |
0.0512 | 13.8 | 690 | 0.6668 | 58.7067 | 51.9929 | 55.5044 | 57.1517 | 20.0 |
0.0397 | 14.0 | 700 | 0.6537 | 58.8717 | 52.4036 | 55.6521 | 57.4855 | 20.0 |
0.0397 | 14.2 | 710 | 0.6463 | 58.9623 | 52.4749 | 55.8145 | 57.8095 | 20.0 |
0.0397 | 14.4 | 720 | 0.6630 | 58.8097 | 52.1997 | 55.8204 | 57.6325 | 20.0 |
0.0397 | 14.6 | 730 | 0.6839 | 59.0479 | 52.6573 | 56.0439 | 57.7322 | 20.0 |
0.0397 | 14.8 | 740 | 0.6541 | 59.2854 | 52.6109 | 56.1891 | 57.9446 | 20.0 |
0.0397 | 15.0 | 750 | 0.6486 | 58.8419 | 52.2004 | 55.8071 | 57.49 | 20.0 |
0.0397 | 15.2 | 760 | 0.6578 | 57.6161 | 50.7276 | 54.5514 | 56.2359 | 20.0 |
0.0397 | 15.4 | 770 | 0.6673 | 57.5458 | 50.8286 | 54.4597 | 56.1513 | 20.0 |
0.0397 | 15.6 | 780 | 0.6624 | 57.6634 | 51.0017 | 54.6769 | 56.3837 | 20.0 |
0.0397 | 15.8 | 790 | 0.6469 | 57.9037 | 51.137 | 54.8939 | 56.6427 | 20.0 |
0.0301 | 16.0 | 800 | 0.6373 | 57.8696 | 51.0899 | 54.8543 | 56.4596 | 20.0 |
0.0301 | 16.2 | 810 | 0.6712 | 58.614 | 52.0052 | 55.6436 | 57.3211 | 20.0 |
0.0301 | 16.4 | 820 | 0.6812 | 58.5214 | 51.8911 | 55.7447 | 57.2663 | 20.0 |
0.0301 | 16.6 | 830 | 0.6716 | 58.5818 | 51.929 | 55.7993 | 57.4064 | 20.0 |
0.0301 | 16.8 | 840 | 0.6590 | 57.745 | 51.0481 | 54.8545 | 56.4781 | 20.0 |
0.0301 | 17.0 | 850 | 0.6695 | 57.6663 | 50.9646 | 54.7863 | 56.3687 | 20.0 |
0.0301 | 17.2 | 860 | 0.6858 | 57.5552 | 51.0436 | 54.7092 | 56.3079 | 20.0 |
0.0301 | 17.4 | 870 | 0.6840 | 57.9091 | 51.3823 | 54.8309 | 56.6186 | 20.0 |
0.0301 | 17.6 | 880 | 0.6751 | 57.8223 | 51.1688 | 54.7562 | 56.5558 | 20.0 |
0.0301 | 17.8 | 890 | 0.6589 | 57.9956 | 51.1425 | 54.9509 | 56.6868 | 20.0 |
0.0482 | 18.0 | 900 | 0.6634 | 58.0392 | 51.3121 | 55.0726 | 56.7878 | 20.0 |
0.0482 | 18.2 | 910 | 0.6907 | 58.2021 | 51.4548 | 55.1874 | 56.91 | 20.0 |
0.0482 | 18.4 | 920 | 0.6977 | 58.1124 | 51.4254 | 55.062 | 56.8412 | 20.0 |
0.0482 | 18.6 | 930 | 0.6832 | 58.0776 | 51.3168 | 55.0849 | 56.8226 | 20.0 |
0.0482 | 18.8 | 940 | 0.6672 | 57.925 | 51.2475 | 54.9661 | 56.655 | 20.0 |
0.0482 | 19.0 | 950 | 0.6582 | 57.9285 | 51.2483 | 54.9744 | 56.6609 | 20.0 |
0.0482 | 19.2 | 960 | 0.6575 | 57.9285 | 51.2483 | 54.9744 | 56.6609 | 20.0 |
0.0482 | 19.4 | 970 | 0.6619 | 57.8961 | 51.2097 | 54.9475 | 56.6344 | 20.0 |
0.0482 | 19.6 | 980 | 0.6658 | 57.8961 | 51.2097 | 54.9475 | 56.6344 | 20.0 |
0.0482 | 19.8 | 990 | 0.6635 | 57.7222 | 51.0096 | 54.8166 | 56.4623 | 20.0 |
0.0201 | 20.0 | 1000 | 0.6617 | 57.7088 | 51.0096 | 54.7514 | 56.3943 | 20.0 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3