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bart-large-cnn-finetuned-roundup-64
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4772
- Rouge1: 46.5444
- Rouge2: 27.4056
- Rougel: 29.6779
- Rougelsum: 44.0905
- Gen Len: 142.0
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 64
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 132 | 1.3213 | 48.3389 | 28.6641 | 31.4086 | 45.6679 | 142.0 |
No log | 2.0 | 264 | 1.2325 | 48.798 | 29.3068 | 31.4329 | 45.7945 | 142.0 |
No log | 3.0 | 396 | 1.2791 | 47.1449 | 27.3965 | 30.56 | 44.4704 | 142.0 |
0.9574 | 4.0 | 528 | 1.3134 | 46.2319 | 25.6249 | 28.7673 | 43.7555 | 140.3 |
0.9574 | 5.0 | 660 | 1.3187 | 46.7313 | 25.3467 | 29.3873 | 43.9495 | 142.0 |
0.9574 | 6.0 | 792 | 1.4271 | 48.1638 | 27.8874 | 30.5334 | 45.9944 | 142.0 |
0.9574 | 7.0 | 924 | 1.4876 | 46.7481 | 25.7259 | 29.7214 | 43.7042 | 140.5 |
0.3303 | 8.0 | 1056 | 1.5259 | 46.7075 | 26.0716 | 29.5521 | 43.7312 | 142.0 |
0.3303 | 9.0 | 1188 | 1.6223 | 48.012 | 27.2795 | 30.4989 | 45.4644 | 142.0 |
0.3303 | 10.0 | 1320 | 1.6842 | 48.0074 | 26.8831 | 29.3396 | 45.1937 | 142.0 |
0.3303 | 11.0 | 1452 | 1.7317 | 46.52 | 26.5152 | 29.5124 | 43.8797 | 142.0 |
0.1478 | 12.0 | 1584 | 1.8087 | 47.5887 | 27.0488 | 29.8569 | 44.7318 | 140.8 |
0.1478 | 13.0 | 1716 | 1.8263 | 46.1251 | 25.8576 | 30.1698 | 42.7228 | 142.0 |
0.1478 | 14.0 | 1848 | 1.9459 | 46.4034 | 25.7039 | 28.2542 | 43.7254 | 142.0 |
0.1478 | 15.0 | 1980 | 1.9539 | 44.4666 | 24.5827 | 27.7147 | 41.9769 | 142.0 |
0.0779 | 16.0 | 2112 | 1.9654 | 47.2267 | 26.4562 | 29.7352 | 44.0823 | 142.0 |
0.0779 | 17.0 | 2244 | 1.9580 | 48.5086 | 28.0294 | 30.8311 | 45.6336 | 142.0 |
0.0779 | 18.0 | 2376 | 2.0065 | 48.293 | 28.5678 | 30.0243 | 45.1384 | 142.0 |
0.0499 | 19.0 | 2508 | 1.9313 | 49.0549 | 28.9695 | 32.0711 | 46.3834 | 142.0 |
0.0499 | 20.0 | 2640 | 2.0176 | 47.0121 | 25.1606 | 29.0108 | 44.1556 | 142.0 |
0.0499 | 21.0 | 2772 | 2.0711 | 48.3754 | 28.2221 | 30.772 | 45.8547 | 140.95 |
0.0499 | 22.0 | 2904 | 2.0848 | 45.7392 | 25.254 | 29.0833 | 43.0381 | 142.0 |
0.0335 | 23.0 | 3036 | 2.0711 | 47.2931 | 27.4573 | 30.718 | 44.5932 | 142.0 |
0.0335 | 24.0 | 3168 | 2.1200 | 50.515 | 30.4253 | 33.7045 | 47.6158 | 142.0 |
0.0335 | 25.0 | 3300 | 2.1097 | 46.4737 | 26.3055 | 29.0148 | 43.2135 | 142.0 |
0.0335 | 26.0 | 3432 | 2.1695 | 46.9099 | 26.5227 | 29.7757 | 44.0613 | 142.0 |
0.0249 | 27.0 | 3564 | 2.1494 | 47.8319 | 27.6364 | 31.3593 | 45.065 | 141.95 |
0.0249 | 28.0 | 3696 | 2.1510 | 47.504 | 26.8971 | 31.7196 | 45.0328 | 142.0 |
0.0249 | 29.0 | 3828 | 2.1612 | 46.8789 | 27.266 | 30.1009 | 43.8248 | 142.0 |
0.0249 | 30.0 | 3960 | 2.1579 | 47.7012 | 27.7761 | 30.935 | 44.3686 | 142.0 |
0.018 | 31.0 | 4092 | 2.1981 | 48.4703 | 29.167 | 31.9815 | 45.8005 | 142.0 |
0.018 | 32.0 | 4224 | 2.2332 | 45.9512 | 25.8111 | 29.2467 | 42.9234 | 142.0 |
0.018 | 33.0 | 4356 | 2.1944 | 47.7189 | 28.1413 | 30.9692 | 44.9361 | 142.0 |
0.018 | 34.0 | 4488 | 2.2589 | 50.9687 | 32.3987 | 36.5644 | 48.3938 | 142.0 |
0.0132 | 35.0 | 4620 | 2.2269 | 47.8241 | 28.0442 | 31.5535 | 44.9394 | 142.0 |
0.0132 | 36.0 | 4752 | 2.2865 | 47.4383 | 27.0825 | 30.4109 | 44.194 | 142.0 |
0.0132 | 37.0 | 4884 | 2.3267 | 49.1786 | 29.6416 | 32.875 | 46.8821 | 142.0 |
0.0095 | 38.0 | 5016 | 2.2872 | 48.2085 | 28.3304 | 32.1473 | 45.3571 | 142.0 |
0.0095 | 39.0 | 5148 | 2.3340 | 46.6762 | 26.1637 | 29.0149 | 43.5923 | 142.0 |
0.0095 | 40.0 | 5280 | 2.3425 | 46.7561 | 26.1645 | 29.6337 | 43.6188 | 142.0 |
0.0095 | 41.0 | 5412 | 2.3111 | 49.4118 | 29.9761 | 33.4765 | 46.601 | 142.0 |
0.0076 | 42.0 | 5544 | 2.3892 | 45.3335 | 25.0161 | 28.4124 | 41.9873 | 142.0 |
0.0076 | 43.0 | 5676 | 2.3808 | 46.2506 | 26.4283 | 29.3841 | 42.7488 | 142.0 |
0.0076 | 44.0 | 5808 | 2.3825 | 45.6823 | 26.0048 | 29.5501 | 42.6475 | 142.0 |
0.0076 | 45.0 | 5940 | 2.3592 | 47.9127 | 26.7924 | 30.2353 | 44.791 | 142.0 |
0.0051 | 46.0 | 6072 | 2.4206 | 46.0415 | 27.0681 | 29.9602 | 43.1225 | 142.0 |
0.0051 | 47.0 | 6204 | 2.4214 | 48.1229 | 29.0913 | 31.1828 | 45.0022 | 142.0 |
0.0051 | 48.0 | 6336 | 2.4176 | 47.3825 | 27.7622 | 30.4138 | 43.9047 | 142.0 |
0.0051 | 49.0 | 6468 | 2.4137 | 48.2544 | 28.277 | 31.5548 | 45.6053 | 142.0 |
0.0041 | 50.0 | 6600 | 2.4384 | 49.6459 | 30.186 | 33.0059 | 47.0483 | 142.0 |
0.0041 | 51.0 | 6732 | 2.4433 | 47.7279 | 27.7857 | 30.2982 | 45.0842 | 142.0 |
0.0041 | 52.0 | 6864 | 2.4068 | 48.6047 | 28.1758 | 31.2744 | 45.8336 | 142.0 |
0.0041 | 53.0 | 6996 | 2.4362 | 48.7095 | 29.3335 | 31.9509 | 46.4161 | 142.0 |
0.003 | 54.0 | 7128 | 2.4307 | 48.836 | 29.6069 | 32.4004 | 46.1986 | 142.0 |
0.003 | 55.0 | 7260 | 2.4292 | 47.2945 | 26.7577 | 28.9719 | 43.8988 | 142.0 |
0.003 | 56.0 | 7392 | 2.4425 | 45.2261 | 25.6879 | 28.8129 | 42.6474 | 142.0 |
0.0024 | 57.0 | 7524 | 2.4386 | 47.967 | 28.5415 | 32.2049 | 45.5111 | 142.0 |
0.0024 | 58.0 | 7656 | 2.4528 | 47.5552 | 27.6397 | 30.9151 | 44.2627 | 142.0 |
0.0024 | 59.0 | 7788 | 2.4574 | 46.7821 | 27.3368 | 30.6334 | 44.0533 | 142.0 |
0.0024 | 60.0 | 7920 | 2.4659 | 47.3507 | 26.8371 | 30.4566 | 44.4452 | 142.0 |
0.0018 | 61.0 | 8052 | 2.4766 | 47.9847 | 28.2678 | 30.0664 | 45.0071 | 142.0 |
0.0018 | 62.0 | 8184 | 2.4682 | 46.8392 | 27.1275 | 30.144 | 43.6379 | 142.0 |
0.0018 | 63.0 | 8316 | 2.4754 | 45.6338 | 26.2812 | 29.4831 | 42.8744 | 142.0 |
0.0018 | 64.0 | 8448 | 2.4772 | 46.5444 | 27.4056 | 29.6779 | 44.0905 | 142.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1