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text_shortening_model_v41
This model is a fine-tuned version of facebook/bart-large-xsum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.7205
- Rouge1: 0.4471
- Rouge2: 0.2088
- Rougel: 0.3939
- Rougelsum: 0.3941
- Bert precision: 0.8647
- Bert recall: 0.8624
- Average word count: 8.6517
- Max word count: 18
- Min word count: 4
- Average token count: 16.5045
- % shortened texts with length > 12: 5.7057
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Bert precision | Bert recall | Average word count | Max word count | Min word count | Average token count | % shortened texts with length > 12 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.424 | 1.0 | 73 | 2.2763 | 0.4466 | 0.2286 | 0.3969 | 0.3973 | 0.8628 | 0.8607 | 8.4805 | 17 | 5 | 14.6967 | 3.6036 |
| 1.331 | 2.0 | 146 | 2.1237 | 0.4671 | 0.2385 | 0.4119 | 0.4124 | 0.86 | 0.8702 | 9.7117 | 20 | 4 | 16.7838 | 14.4144 |
| 0.9725 | 3.0 | 219 | 1.9947 | 0.448 | 0.2384 | 0.4004 | 0.4025 | 0.8603 | 0.8627 | 8.8649 | 16 | 5 | 15.8709 | 5.7057 |
| 0.7753 | 4.0 | 292 | 2.2302 | 0.4435 | 0.2201 | 0.3983 | 0.3991 | 0.8653 | 0.8588 | 8.1141 | 16 | 5 | 15.5526 | 1.8018 |
| 0.6017 | 5.0 | 365 | 2.1392 | 0.4293 | 0.2142 | 0.383 | 0.3836 | 0.8593 | 0.8604 | 8.6156 | 17 | 4 | 14.1982 | 3.3033 |
| 0.4911 | 6.0 | 438 | 2.4747 | 0.4166 | 0.1882 | 0.365 | 0.3668 | 0.8582 | 0.8556 | 8.4234 | 14 | 5 | 14.4024 | 3.6036 |
| 0.6947 | 7.0 | 511 | 2.6372 | 0.3894 | 0.1904 | 0.3527 | 0.3534 | 0.8471 | 0.8477 | 8.5165 | 14 | 4 | 16.6607 | 4.2042 |
| 0.5839 | 8.0 | 584 | 2.6038 | 0.3641 | 0.1627 | 0.3272 | 0.3276 | 0.8464 | 0.8402 | 7.7508 | 13 | 4 | 15.2342 | 0.6006 |
| 0.4668 | 9.0 | 657 | 2.7711 | 0.4015 | 0.1904 | 0.3627 | 0.3626 | 0.8537 | 0.8517 | 8.8889 | 17 | 4 | 16.2402 | 3.9039 |
| 0.4539 | 10.0 | 730 | 2.8819 | 0.4 | 0.1903 | 0.353 | 0.3538 | 0.8526 | 0.8519 | 8.6156 | 15 | 5 | 16.1652 | 3.9039 |
| 0.4018 | 11.0 | 803 | 2.8273 | 0.3799 | 0.1764 | 0.3404 | 0.3407 | 0.8432 | 0.8454 | 8.7177 | 17 | 4 | 17.0661 | 3.6036 |
| 0.2764 | 12.0 | 876 | 2.9767 | 0.3888 | 0.1825 | 0.3504 | 0.3509 | 0.8526 | 0.8475 | 8.4354 | 13 | 5 | 16.015 | 2.1021 |
| 0.2338 | 13.0 | 949 | 2.8883 | 0.4184 | 0.202 | 0.3714 | 0.3714 | 0.852 | 0.8585 | 9.3754 | 17 | 5 | 15.8709 | 8.4084 |
| 0.1878 | 14.0 | 1022 | 3.1069 | 0.4302 | 0.1966 | 0.3782 | 0.3791 | 0.8616 | 0.8573 | 8.4324 | 15 | 4 | 16.2492 | 3.3033 |
| 0.1608 | 15.0 | 1095 | 2.8510 | 0.4461 | 0.2151 | 0.392 | 0.3925 | 0.8627 | 0.8625 | 8.7598 | 19 | 4 | 16.1471 | 5.7057 |
| 0.1416 | 16.0 | 1168 | 3.0792 | 0.4246 | 0.1983 | 0.3735 | 0.3735 | 0.8591 | 0.8568 | 8.6637 | 16 | 5 | 16.3303 | 7.5075 |
| 0.1507 | 17.0 | 1241 | 3.2058 | 0.4336 | 0.2016 | 0.379 | 0.3796 | 0.8593 | 0.8589 | 8.9129 | 17 | 5 | 16.6697 | 5.1051 |
| 0.108 | 18.0 | 1314 | 3.0551 | 0.4485 | 0.2248 | 0.4002 | 0.4006 | 0.8645 | 0.8608 | 8.2492 | 14 | 5 | 15.967 | 3.6036 |
| 0.0756 | 19.0 | 1387 | 3.1943 | 0.4439 | 0.2167 | 0.3919 | 0.3925 | 0.8652 | 0.8608 | 8.4865 | 15 | 5 | 15.8919 | 3.9039 |
| 0.104 | 20.0 | 1460 | 3.1156 | 0.4411 | 0.2035 | 0.3894 | 0.3903 | 0.8644 | 0.8612 | 8.5135 | 16 | 5 | 16.4294 | 6.006 |
| 0.0716 | 21.0 | 1533 | 3.4040 | 0.4389 | 0.201 | 0.3824 | 0.3838 | 0.8632 | 0.8614 | 8.7508 | 16 | 4 | 16.5075 | 6.006 |
| 0.0576 | 22.0 | 1606 | 3.4264 | 0.4476 | 0.2104 | 0.3902 | 0.391 | 0.8657 | 0.8629 | 8.5405 | 16 | 4 | 16.4144 | 6.6066 |
| 0.041 | 23.0 | 1679 | 3.5711 | 0.447 | 0.2108 | 0.3931 | 0.393 | 0.8639 | 0.8619 | 8.5976 | 18 | 4 | 16.4264 | 7.2072 |
| 0.0355 | 24.0 | 1752 | 3.6294 | 0.4509 | 0.215 | 0.3981 | 0.3989 | 0.8652 | 0.8632 | 8.6186 | 18 | 4 | 16.4985 | 6.006 |
| 0.0313 | 25.0 | 1825 | 3.7205 | 0.4471 | 0.2088 | 0.3939 | 0.3941 | 0.8647 | 0.8624 | 8.6517 | 18 | 4 | 16.5045 | 5.7057 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
