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arthurmluz
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ptt5-xlsumm-gptextsum

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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arthurmluz commited on
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0790926
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  1. README.md +36 -36
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [arthurmluz/ptt5-xlsumm-30epochs](https://huggingface.co/arthurmluz/ptt5-xlsumm-30epochs) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.2170
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- - Rouge1: 0.4041
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- - Rouge2: 0.207
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- - Rougel: 0.3276
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- - Rougelsum: 0.3632
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- - Gen Len: 18.875
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  ## Model description
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@@ -53,36 +53,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | No log | 1.0 | 70 | 2.3635 | 0.318 | 0.1516 | 0.2478 | 0.2858 | 18.675 |
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- | No log | 2.0 | 140 | 2.1986 | 0.3333 | 0.1619 | 0.268 | 0.3003 | 18.7 |
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- | 2.3332 | 3.0 | 210 | 2.1209 | 0.3244 | 0.1429 | 0.2551 | 0.293 | 18.5 |
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- | 2.3332 | 4.0 | 280 | 2.0820 | 0.3448 | 0.1618 | 0.2703 | 0.3098 | 18.5 |
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- | 2.3332 | 5.0 | 350 | 2.0565 | 0.3502 | 0.1769 | 0.2756 | 0.3135 | 18.75 |
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- | 1.785 | 6.0 | 420 | 2.0446 | 0.3541 | 0.1808 | 0.2734 | 0.3169 | 18.825 |
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- | 1.785 | 7.0 | 490 | 2.0435 | 0.3628 | 0.1867 | 0.2843 | 0.3228 | 18.75 |
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- | 1.785 | 8.0 | 560 | 2.0482 | 0.3679 | 0.1886 | 0.2918 | 0.3314 | 18.725 |
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- | 1.4946 | 9.0 | 630 | 2.0481 | 0.3741 | 0.1869 | 0.2949 | 0.3336 | 18.85 |
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- | 1.4946 | 10.0 | 700 | 2.0494 | 0.379 | 0.1979 | 0.3012 | 0.338 | 18.8 |
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- | 1.4946 | 11.0 | 770 | 2.0602 | 0.3786 | 0.196 | 0.3045 | 0.3342 | 18.8 |
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- | 1.2836 | 12.0 | 840 | 2.0691 | 0.3749 | 0.1971 | 0.3012 | 0.3352 | 18.85 |
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- | 1.2836 | 13.0 | 910 | 2.0795 | 0.3789 | 0.1953 | 0.3082 | 0.3371 | 18.8 |
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- | 1.2836 | 14.0 | 980 | 2.0898 | 0.3809 | 0.196 | 0.3052 | 0.3378 | 18.825 |
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- | 1.1472 | 15.0 | 1050 | 2.1076 | 0.3904 | 0.1979 | 0.3137 | 0.3462 | 18.875 |
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- | 1.1472 | 16.0 | 1120 | 2.1109 | 0.3905 | 0.1929 | 0.3101 | 0.3436 | 18.875 |
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- | 1.1472 | 17.0 | 1190 | 2.1253 | 0.4046 | 0.2029 | 0.3242 | 0.3594 | 18.875 |
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- | 1.0175 | 18.0 | 1260 | 2.1418 | 0.4093 | 0.2074 | 0.3255 | 0.3614 | 18.875 |
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- | 1.0175 | 19.0 | 1330 | 2.1578 | 0.4065 | 0.213 | 0.3289 | 0.363 | 18.875 |
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- | 0.9398 | 20.0 | 1400 | 2.1593 | 0.4125 | 0.2197 | 0.333 | 0.3716 | 18.875 |
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- | 0.9398 | 21.0 | 1470 | 2.1663 | 0.4091 | 0.2111 | 0.3282 | 0.368 | 18.875 |
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- | 0.9398 | 22.0 | 1540 | 2.1775 | 0.4081 | 0.2111 | 0.3301 | 0.366 | 18.875 |
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- | 0.8644 | 23.0 | 1610 | 2.1889 | 0.4015 | 0.206 | 0.3274 | 0.3613 | 18.875 |
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- | 0.8644 | 24.0 | 1680 | 2.1932 | 0.4015 | 0.206 | 0.3274 | 0.3613 | 18.875 |
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- | 0.8644 | 25.0 | 1750 | 2.2016 | 0.4075 | 0.2089 | 0.331 | 0.3672 | 18.875 |
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- | 0.8385 | 26.0 | 1820 | 2.2058 | 0.4082 | 0.2087 | 0.33 | 0.3688 | 18.875 |
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- | 0.8385 | 27.0 | 1890 | 2.2089 | 0.4075 | 0.2089 | 0.331 | 0.3672 | 18.875 |
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- | 0.8385 | 28.0 | 1960 | 2.2131 | 0.4061 | 0.2079 | 0.3286 | 0.3651 | 18.875 |
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- | 0.7999 | 29.0 | 2030 | 2.2161 | 0.4061 | 0.2079 | 0.3286 | 0.3651 | 18.875 |
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- | 0.7999 | 30.0 | 2100 | 2.2170 | 0.4041 | 0.207 | 0.3276 | 0.3632 | 18.875 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [arthurmluz/ptt5-xlsumm-30epochs](https://huggingface.co/arthurmluz/ptt5-xlsumm-30epochs) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1132
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+ - Rouge1: 0.1715
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+ - Rouge2: 0.0919
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+ - Rougel: 0.1417
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+ - Rougelsum: 0.1611
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+ - Gen Len: 19.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 70 | 2.3037 | 0.1617 | 0.0691 | 0.1287 | 0.1467 | 19.0 |
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+ | No log | 2.0 | 140 | 2.2106 | 0.1722 | 0.082 | 0.1362 | 0.1585 | 19.0 |
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+ | 2.3539 | 3.0 | 210 | 2.1604 | 0.1738 | 0.0854 | 0.1387 | 0.1604 | 19.0 |
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+ | 2.3539 | 4.0 | 280 | 2.1325 | 0.1727 | 0.0868 | 0.1407 | 0.1632 | 19.0 |
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+ | 2.3539 | 5.0 | 350 | 2.1117 | 0.1707 | 0.0875 | 0.137 | 0.1603 | 19.0 |
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+ | 2.0032 | 6.0 | 420 | 2.0957 | 0.1723 | 0.0907 | 0.1415 | 0.1607 | 19.0 |
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+ | 2.0032 | 7.0 | 490 | 2.0848 | 0.1722 | 0.09 | 0.1414 | 0.1617 | 19.0 |
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+ | 2.0032 | 8.0 | 560 | 2.0790 | 0.1757 | 0.0918 | 0.1429 | 0.164 | 19.0 |
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+ | 1.8158 | 9.0 | 630 | 2.0800 | 0.1723 | 0.0929 | 0.1421 | 0.1614 | 19.0 |
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+ | 1.8158 | 10.0 | 700 | 2.0736 | 0.1733 | 0.0923 | 0.1428 | 0.1617 | 19.0 |
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+ | 1.8158 | 11.0 | 770 | 2.0721 | 0.1755 | 0.0955 | 0.1454 | 0.1631 | 19.0 |
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+ | 1.6764 | 12.0 | 840 | 2.0784 | 0.1763 | 0.0973 | 0.1459 | 0.1637 | 19.0 |
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+ | 1.6764 | 13.0 | 910 | 2.0761 | 0.1752 | 0.094 | 0.1456 | 0.1638 | 19.0 |
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+ | 1.6764 | 14.0 | 980 | 2.0802 | 0.1745 | 0.0951 | 0.145 | 0.1631 | 19.0 |
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+ | 1.5616 | 15.0 | 1050 | 2.0790 | 0.1745 | 0.0952 | 0.1458 | 0.1632 | 19.0 |
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+ | 1.5616 | 16.0 | 1120 | 2.0841 | 0.1735 | 0.0946 | 0.1447 | 0.1629 | 19.0 |
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+ | 1.5616 | 17.0 | 1190 | 2.0904 | 0.1731 | 0.0943 | 0.1444 | 0.1622 | 19.0 |
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+ | 1.4821 | 18.0 | 1260 | 2.0909 | 0.1727 | 0.0934 | 0.1433 | 0.1613 | 19.0 |
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+ | 1.4821 | 19.0 | 1330 | 2.0934 | 0.1738 | 0.0948 | 0.1448 | 0.1632 | 19.0 |
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+ | 1.4256 | 20.0 | 1400 | 2.0948 | 0.1726 | 0.0935 | 0.1434 | 0.1621 | 19.0 |
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+ | 1.4256 | 21.0 | 1470 | 2.0981 | 0.173 | 0.0942 | 0.1435 | 0.1621 | 19.0 |
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+ | 1.4256 | 22.0 | 1540 | 2.1023 | 0.1734 | 0.0945 | 0.1445 | 0.1631 | 19.0 |
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+ | 1.3691 | 23.0 | 1610 | 2.1048 | 0.1726 | 0.0941 | 0.1436 | 0.1616 | 19.0 |
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+ | 1.3691 | 24.0 | 1680 | 2.1058 | 0.1721 | 0.0948 | 0.1435 | 0.1619 | 19.0 |
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+ | 1.3691 | 25.0 | 1750 | 2.1095 | 0.1721 | 0.0945 | 0.1435 | 0.1619 | 19.0 |
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+ | 1.3444 | 26.0 | 1820 | 2.1103 | 0.1721 | 0.0948 | 0.1436 | 0.1624 | 19.0 |
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+ | 1.3444 | 27.0 | 1890 | 2.1113 | 0.1715 | 0.0923 | 0.1417 | 0.1611 | 19.0 |
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+ | 1.3444 | 28.0 | 1960 | 2.1121 | 0.1715 | 0.0919 | 0.1417 | 0.1611 | 19.0 |
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+ | 1.3145 | 29.0 | 2030 | 2.1130 | 0.172 | 0.093 | 0.1425 | 0.1619 | 19.0 |
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+ | 1.3145 | 30.0 | 2100 | 2.1132 | 0.1715 | 0.0919 | 0.1417 | 0.1611 | 19.0 |
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  ### Framework versions
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