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cnn_dailymail-summarization-t5-small-2022-09-05
This model is a fine-tuned version of t5-small on the cnn_dailymail 3.0.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6455
- Rouge1: 41.4235
- Rouge2: 19.0263
- Rougel: 29.2892
- Rougelsum: 38.6338
- Gen Len: 73.7273
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: 3.0
Training results
| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|---|
| 1.9623 | 0.03 | 1000 | 18.9996 | 1.7500 | 24.1039 | 11.368 | 19.813 | 22.671 |
| 1.8827 | 0.06 | 2000 | 18.9993 | 1.7382 | 24.1445 | 11.4497 | 19.8683 | 22.7376 |
| 1.8988 | 0.08 | 3000 | 18.9999 | 1.7310 | 24.329 | 11.5899 | 20.0409 | 22.9104 |
| 1.8778 | 0.11 | 4000 | 19.0 | 1.7177 | 24.3886 | 11.6472 | 20.1048 | 22.988 |
| 1.9173 | 0.14 | 5000 | 18.9996 | 1.7140 | 24.3508 | 11.5594 | 20.075 | 22.932 |
| 1.9009 | 0.17 | 6000 | 18.9995 | 1.7134 | 24.28 | 11.6075 | 20.0581 | 22.8833 |
| 1.8975 | 0.2 | 7000 | 18.9994 | 1.7081 | 24.3203 | 11.6175 | 20.035 | 22.9167 |
| 1.8835 | 0.22 | 8000 | 18.9996 | 1.7061 | 24.2729 | 11.6324 | 20.0728 | 22.8747 |
| 1.8725 | 0.25 | 9000 | 19.0 | 1.6995 | 24.2542 | 11.5763 | 20.0241 | 22.8713 |
| 1.837 | 0.28 | 10000 | 18.9997 | 1.6998 | 24.3321 | 11.599 | 20.1028 | 22.9562 |
| 1.8629 | 0.31 | 11000 | 19.0 | 1.6944 | 24.4161 | 11.6208 | 20.1374 | 23.024 |
| 1.85 | 0.33 | 12000 | 18.9990 | 1.7002 | 24.3514 | 11.6883 | 20.134 | 22.9515 |
| 1.8506 | 0.36 | 13000 | 18.9987 | 1.6894 | 24.3812 | 11.6592 | 20.1641 | 23.0108 |
| 1.8869 | 0.39 | 14000 | 18.9995 | 1.6881 | 24.3956 | 11.6817 | 20.1654 | 23.0284 |
| 1.8327 | 0.42 | 15000 | 18.9993 | 1.6903 | 24.3707 | 11.6446 | 20.1353 | 22.9801 |
| 1.8204 | 0.45 | 16000 | 18.9993 | 1.6896 | 24.3663 | 11.6963 | 20.1357 | 22.9898 |
| 1.8764 | 0.47 | 17000 | 18.9978 | 1.6846 | 24.4212 | 11.652 | 20.1455 | 23.0326 |
| 1.8213 | 0.5 | 18000 | 18.9992 | 1.6817 | 24.452 | 11.7014 | 20.1898 | 23.0668 |
| 1.8424 | 0.53 | 19000 | 18.9990 | 1.6844 | 24.4206 | 11.7049 | 20.1931 | 23.0358 |
| 1.8721 | 0.56 | 20000 | 18.9996 | 1.6814 | 24.4483 | 11.6789 | 20.1798 | 23.0508 |
| 1.87 | 0.59 | 21000 | 18.9996 | 1.6796 | 24.4799 | 11.6789 | 20.1919 | 23.0831 |
| 1.844 | 0.61 | 22000 | 18.9996 | 1.6770 | 24.4741 | 11.7433 | 20.2031 | 23.0535 |
| 1.8611 | 0.64 | 23000 | 18.9986 | 1.6785 | 24.4837 | 11.7572 | 20.219 | 23.088 |
| 1.8201 | 0.67 | 24000 | 18.9993 | 1.6796 | 24.3955 | 11.6978 | 20.173 | 23.0302 |
| 1.8506 | 0.7 | 25000 | 18.9995 | 1.6770 | 24.4084 | 11.711 | 20.1851 | 23.0266 |
| 1.846 | 0.72 | 26000 | 18.9990 | 1.6765 | 24.4272 | 11.6779 | 20.1785 | 23.0352 |
| 1.8431 | 0.75 | 27000 | 18.9998 | 1.6757 | 24.4484 | 11.7154 | 20.2156 | 23.0646 |
| 1.8208 | 0.78 | 28000 | 18.9993 | 1.6764 | 24.412 | 11.6887 | 20.1752 | 23.0151 |
| 1.8108 | 0.81 | 29000 | 18.9997 | 1.6733 | 24.4051 | 11.7155 | 20.1773 | 23.0215 |
| 1.847 | 0.84 | 30000 | 18.9994 | 1.6738 | 24.5531 | 11.7949 | 20.2834 | 23.1588 |
| 1.8386 | 0.86 | 31000 | 18.9991 | 1.6674 | 24.5155 | 11.7333 | 20.2529 | 23.145 |
| 1.82 | 0.89 | 32000 | 18.9988 | 1.6693 | 24.4498 | 11.7118 | 20.2183 | 23.0767 |
| 1.8475 | 0.92 | 33000 | 18.9993 | 1.6676 | 24.442 | 11.676 | 20.168 | 23.0409 |
| 1.7948 | 0.95 | 34000 | 18.9990 | 1.6689 | 24.4561 | 11.7865 | 20.2446 | 23.0707 |
| 1.8357 | 0.98 | 35000 | 18.9994 | 1.6757 | 24.4005 | 11.7299 | 20.1999 | 23.0093 |
| 1.8624 | 1.0 | 36000 | 18.9988 | 1.6745 | 24.3371 | 11.6749 | 20.1257 | 22.9428 |
| 1.8309 | 1.03 | 37000 | 18.9995 | 1.6675 | 24.5108 | 11.8038 | 20.2691 | 23.117 |
| 1.8237 | 1.06 | 38000 | 18.9996 | 1.6654 | 24.482 | 11.7485 | 20.2225 | 23.0917 |
| 1.7743 | 1.09 | 39000 | 18.9993 | 1.6681 | 24.5106 | 11.7511 | 20.2583 | 23.123 |
| 1.7811 | 1.11 | 40000 | 18.9991 | 1.6636 | 24.6194 | 11.843 | 20.3375 | 23.2259 |
| 1.7973 | 1.14 | 41000 | 19.0 | 1.6666 | 24.5434 | 11.8133 | 20.3033 | 23.165 |
| 1.8156 | 1.17 | 42000 | 18.9993 | 1.6660 | 24.4857 | 11.7526 | 20.2406 | 23.1081 |
| 1.8403 | 1.2 | 43000 | 18.9998 | 1.6621 | 24.4632 | 11.7525 | 20.2459 | 23.0692 |
| 1.8129 | 1.23 | 44000 | 18.9999 | 1.6643 | 24.6032 | 11.8251 | 20.3368 | 23.1806 |
| 1.7896 | 1.25 | 45000 | 18.9993 | 1.6622 | 24.4619 | 11.7769 | 20.2516 | 23.0647 |
| 1.7948 | 1.28 | 46000 | 18.9992 | 1.6608 | 24.5468 | 11.8041 | 20.2941 | 23.1551 |
| 1.8043 | 1.31 | 47000 | 18.9993 | 1.6614 | 24.5774 | 11.8246 | 20.3189 | 23.1836 |
| 1.7884 | 1.34 | 48000 | 18.9993 | 1.6581 | 24.5688 | 11.843 | 20.2993 | 23.1756 |
| 1.8041 | 1.37 | 49000 | 18.9996 | 1.6614 | 24.5454 | 11.8346 | 20.3179 | 23.1605 |
| 1.8192 | 1.39 | 50000 | 18.9998 | 1.6597 | 24.5017 | 11.7755 | 20.2439 | 23.1148 |
| 1.8679 | 1.42 | 51000 | 18.9995 | 1.6555 | 24.5302 | 11.7638 | 20.2592 | 23.1395 |
| 1.82 | 1.45 | 52000 | 18.9998 | 1.6571 | 24.546 | 11.7798 | 20.265 | 23.1408 |
| 1.8267 | 1.48 | 53000 | 18.9996 | 1.6552 | 24.5214 | 11.7368 | 20.2276 | 23.1504 |
| 1.8063 | 1.5 | 54000 | 18.9992 | 1.6588 | 24.5222 | 11.8209 | 20.2941 | 23.1551 |
| 1.8171 | 1.53 | 55000 | 18.9996 | 1.6569 | 24.5845 | 11.8182 | 20.3147 | 23.1812 |
| 1.7884 | 1.56 | 56000 | 18.9998 | 1.6597 | 24.532 | 11.8057 | 20.2622 | 23.1459 |
| 1.7588 | 1.59 | 57000 | 18.9994 | 1.6572 | 24.6532 | 11.8958 | 20.3877 | 23.2776 |
| 1.7847 | 1.62 | 58000 | 18.9996 | 1.6561 | 24.5483 | 11.856 | 20.3188 | 23.1852 |
| 1.8523 | 1.64 | 59000 | 18.9996 | 1.6584 | 24.5501 | 11.8666 | 20.3197 | 23.1683 |
| 1.7955 | 1.67 | 60000 | 18.9999 | 1.6546 | 24.5126 | 11.8043 | 20.2603 | 23.1175 |
| 1.8215 | 1.7 | 61000 | 18.9996 | 1.6541 | 24.5884 | 11.8003 | 20.2887 | 23.1866 |
| 1.7917 | 1.73 | 62000 | 18.9997 | 1.6568 | 24.619 | 11.8868 | 20.3496 | 23.2304 |
| 1.7543 | 1.76 | 63000 | 18.9996 | 1.6570 | 24.5378 | 11.8192 | 20.2681 | 23.1454 |
| 1.7978 | 1.78 | 64000 | 18.9999 | 1.6541 | 24.5719 | 11.8446 | 20.2873 | 23.1855 |
| 1.8228 | 1.81 | 65000 | 18.9998 | 1.6561 | 24.5193 | 11.8527 | 20.3185 | 23.1395 |
| 1.8163 | 1.84 | 66000 | 18.9998 | 1.6537 | 24.4385 | 11.7625 | 20.2042 | 23.0671 |
| 1.7868 | 1.87 | 67000 | 18.9998 | 1.6532 | 24.4985 | 11.8187 | 20.2775 | 23.1426 |
| 1.8345 | 1.89 | 68000 | 18.9999 | 1.6522 | 24.5375 | 11.8398 | 20.285 | 23.1643 |
| 1.7773 | 1.92 | 69000 | 18.9999 | 1.6529 | 24.4722 | 11.7979 | 20.2636 | 23.106 |
| 1.8409 | 1.95 | 70000 | 18.9999 | 1.6521 | 24.4845 | 11.8136 | 20.2557 | 23.1089 |
| 1.8146 | 1.98 | 71000 | 18.9999 | 1.6515 | 24.4923 | 11.7965 | 20.2521 | 23.1247 |
| 1.7466 | 2.01 | 72000 | 19.0 | 1.6526 | 24.4913 | 11.8254 | 20.2562 | 23.1266 |
| 1.8009 | 2.03 | 73000 | 19.0 | 1.6505 | 24.5231 | 11.8414 | 20.2842 | 23.1654 |
| 1.7768 | 2.06 | 74000 | 19.0 | 1.6516 | 24.5192 | 11.8206 | 20.2884 | 23.1493 |
| 1.7569 | 2.09 | 75000 | 19.0 | 1.6541 | 24.6135 | 11.9135 | 20.3513 | 23.2279 |
| 1.7893 | 2.12 | 76000 | 18.9997 | 1.6507 | 24.5934 | 11.8727 | 20.3305 | 23.2106 |
| 1.763 | 2.15 | 77000 | 18.9999 | 1.6512 | 24.5829 | 11.8543 | 20.3142 | 23.2049 |
| 1.7552 | 2.17 | 78000 | 18.9998 | 1.6506 | 24.5332 | 11.8309 | 20.2795 | 23.1654 |
| 1.7632 | 2.2 | 79000 | 18.9995 | 1.6498 | 24.5569 | 11.8313 | 20.3158 | 23.1808 |
| 1.8056 | 2.23 | 80000 | 18.9996 | 1.6488 | 24.6217 | 11.8877 | 20.3555 | 23.2514 |
| 1.8066 | 2.26 | 81000 | 18.9996 | 1.6494 | 24.5799 | 11.8515 | 20.3307 | 23.2059 |
| 1.7903 | 2.28 | 82000 | 18.9998 | 1.6487 | 24.6151 | 11.889 | 20.3739 | 23.2226 |
| 1.805 | 2.31 | 83000 | 18.9996 | 1.6493 | 24.5739 | 11.8659 | 20.3354 | 23.1884 |
| 1.7843 | 2.34 | 84000 | 18.9996 | 1.6487 | 24.6125 | 11.8879 | 20.3648 | 23.2274 |
| 1.8153 | 2.37 | 85000 | 18.9996 | 1.6493 | 24.5638 | 11.8392 | 20.3084 | 23.165 |
| 1.7581 | 2.4 | 86000 | 18.9996 | 1.6490 | 24.6121 | 11.8876 | 20.36 | 23.2163 |
| 1.6925 | 2.42 | 87000 | 18.9998 | 1.6502 | 24.6192 | 11.8992 | 20.3786 | 23.2421 |
| 1.7535 | 2.45 | 88000 | 18.9996 | 1.6473 | 24.6134 | 11.8877 | 20.3663 | 23.2262 |
| 1.751 | 2.48 | 89000 | 18.9996 | 1.6496 | 24.5728 | 11.8886 | 20.3411 | 23.1906 |
| 1.7577 | 2.51 | 90000 | 18.9996 | 1.6477 | 24.5616 | 11.8489 | 20.3021 | 23.1754 |
| 1.8 | 2.54 | 91000 | 18.9996 | 1.6473 | 24.5614 | 11.8663 | 20.3282 | 23.1868 |
| 1.7859 | 2.56 | 92000 | 18.9998 | 1.6483 | 24.5594 | 11.8426 | 20.3197 | 23.191 |
| 1.7984 | 2.59 | 93000 | 18.9998 | 1.6469 | 24.5732 | 11.8258 | 20.3204 | 23.1958 |
| 1.7943 | 2.62 | 94000 | 18.9996 | 1.6477 | 24.5888 | 11.8602 | 20.3352 | 23.2181 |
| 1.7888 | 2.65 | 95000 | 18.9996 | 1.6472 | 24.5781 | 11.844 | 20.3272 | 23.216 |
| 1.7803 | 2.67 | 96000 | 1.6483 | 24.5454 | 11.8245 | 20.2917 | 23.1727 | 18.9996 |
| 1.8106 | 2.7 | 97000 | 1.6461 | 24.5694 | 11.8344 | 20.3123 | 23.1934 | 18.9996 |
| 1.8713 | 2.73 | 98000 | 1.6454 | 24.5906 | 11.8573 | 20.3447 | 23.2181 | 18.9996 |
| 1.7655 | 2.76 | 99000 | 1.6468 | 24.5709 | 11.8573 | 20.3139 | 23.1994 | 18.9996 |
| 1.7616 | 2.79 | 100000 | 1.6464 | 24.5852 | 11.8531 | 20.3172 | 23.2089 | 18.9998 |
| 1.7581 | 2.81 | 101000 | 1.6468 | 24.5748 | 11.8452 | 20.3043 | 23.1849 | 18.9997 |
| 1.7743 | 2.84 | 102000 | 1.6462 | 24.5665 | 11.8328 | 20.2992 | 23.1896 | 18.9996 |
| 1.78 | 2.87 | 103000 | 1.6458 | 24.5716 | 11.8399 | 20.31 | 23.1943 | 18.9996 |
| 1.8162 | 2.9 | 104000 | 1.6456 | 24.5719 | 11.8358 | 20.3132 | 23.1921 | 18.9996 |
| 1.7862 | 2.93 | 105000 | 1.6462 | 24.5938 | 11.8624 | 20.337 | 23.2131 | 18.9996 |
| 1.7995 | 2.95 | 106000 | 1.6459 | 24.5885 | 11.8606 | 20.3325 | 23.2137 | 18.9996 |
| 1.7559 | 2.98 | 107000 | 1.6454 | 24.593 | 11.861 | 20.3401 | 23.2188 | 18.9996 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
