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3_loa

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@@ -10,7 +10,6 @@ metrics:
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  model-index:
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  - name: 3_loa
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  results: []
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- library_name: peft
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the billsum dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5159
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- - Rouge1: 0.2005
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- - Rouge2: 0.1122
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- - Rougel: 0.1739
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- - Rougelsum: 0.1738
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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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- | 2.0741 | 1.0 | 989 | 1.7085 | 0.2064 | 0.1145 | 0.1771 | 0.1771 | 19.0 |
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- | 1.8521 | 2.0 | 1978 | 1.6510 | 0.2021 | 0.109 | 0.1744 | 0.1743 | 19.0 |
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- | 1.7753 | 3.0 | 2967 | 1.6182 | 0.2015 | 0.1099 | 0.1742 | 0.1742 | 19.0 |
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- | 1.7481 | 4.0 | 3956 | 1.5940 | 0.1995 | 0.1102 | 0.1736 | 0.1737 | 19.0 |
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- | 1.6966 | 5.0 | 4945 | 1.5771 | 0.1999 | 0.1112 | 0.1739 | 0.1738 | 19.0 |
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- | 1.7107 | 6.0 | 5934 | 1.5629 | 0.1974 | 0.1091 | 0.1721 | 0.1721 | 19.0 |
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- | 1.6905 | 7.0 | 6923 | 1.5527 | 0.1993 | 0.1091 | 0.1737 | 0.1737 | 19.0 |
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- | 1.6341 | 8.0 | 7912 | 1.5475 | 0.1994 | 0.11 | 0.1732 | 0.1731 | 19.0 |
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- | 1.6649 | 9.0 | 8901 | 1.5422 | 0.1978 | 0.109 | 0.1726 | 0.1722 | 19.0 |
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- | 1.6338 | 10.0 | 9890 | 1.5339 | 0.2009 | 0.1125 | 0.1748 | 0.1744 | 19.0 |
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- | 1.6545 | 11.0 | 10879 | 1.5310 | 0.201 | 0.1138 | 0.1759 | 0.1757 | 19.0 |
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- | 1.6617 | 12.0 | 11868 | 1.5323 | 0.2026 | 0.1152 | 0.1762 | 0.1761 | 19.0 |
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- | 1.629 | 13.0 | 12857 | 1.5245 | 0.202 | 0.1143 | 0.1752 | 0.1751 | 19.0 |
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- | 1.6202 | 14.0 | 13846 | 1.5214 | 0.2021 | 0.1138 | 0.1752 | 0.1751 | 19.0 |
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- | 1.6127 | 15.0 | 14835 | 1.5206 | 0.2013 | 0.113 | 0.1746 | 0.1743 | 19.0 |
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- | 1.6072 | 16.0 | 15824 | 1.5171 | 0.1991 | 0.1112 | 0.1731 | 0.1727 | 19.0 |
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- | 1.6032 | 17.0 | 16813 | 1.5180 | 0.1997 | 0.1126 | 0.1737 | 0.1735 | 19.0 |
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- | 1.6103 | 18.0 | 17802 | 1.5169 | 0.1999 | 0.1128 | 0.1741 | 0.1738 | 19.0 |
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- | 1.5956 | 19.0 | 18791 | 1.5160 | 0.2008 | 0.1128 | 0.1743 | 0.174 | 19.0 |
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- | 1.5981 | 20.0 | 19780 | 1.5159 | 0.2005 | 0.1122 | 0.1739 | 0.1738 | 19.0 |
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  ### Framework versions
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- - PEFT 0.4.0
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  - Transformers 4.31.0
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  - Pytorch 1.13.1.post200
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  - Datasets 2.10.0
 
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  model-index:
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  - name: 3_loa
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  results: []
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the billsum dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4825
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+ - Rouge1: 0.201
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+ - Rouge2: 0.1132
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+ - Rougel: 0.1753
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+ - Rougelsum: 0.1755
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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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+ | 2.1079 | 1.0 | 989 | 1.6673 | 0.2028 | 0.1092 | 0.1748 | 0.1751 | 19.0 |
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+ | 1.8481 | 2.0 | 1978 | 1.6150 | 0.1979 | 0.1061 | 0.1715 | 0.1717 | 19.0 |
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+ | 1.7889 | 3.0 | 2967 | 1.5833 | 0.1994 | 0.11 | 0.1727 | 0.1727 | 19.0 |
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+ | 1.7319 | 4.0 | 3956 | 1.5584 | 0.1978 | 0.1084 | 0.1718 | 0.1718 | 19.0 |
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+ | 1.7279 | 5.0 | 4945 | 1.5440 | 0.2016 | 0.1106 | 0.1755 | 0.1756 | 19.0 |
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+ | 1.7386 | 6.0 | 5934 | 1.5326 | 0.1991 | 0.1086 | 0.1734 | 0.1736 | 19.0 |
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+ | 1.6972 | 7.0 | 6923 | 1.5251 | 0.2013 | 0.1122 | 0.1759 | 0.176 | 19.0 |
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+ | 1.6732 | 8.0 | 7912 | 1.5145 | 0.2024 | 0.1123 | 0.1766 | 0.1766 | 19.0 |
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+ | 1.6597 | 9.0 | 8901 | 1.5079 | 0.2019 | 0.1125 | 0.1751 | 0.1753 | 19.0 |
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+ | 1.6151 | 10.0 | 9890 | 1.5045 | 0.201 | 0.1123 | 0.1758 | 0.1761 | 19.0 |
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+ | 1.6381 | 11.0 | 10879 | 1.4997 | 0.2009 | 0.1116 | 0.1755 | 0.1756 | 19.0 |
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+ | 1.6148 | 12.0 | 11868 | 1.4974 | 0.2018 | 0.1133 | 0.1763 | 0.1765 | 19.0 |
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+ | 1.6196 | 13.0 | 12857 | 1.4940 | 0.2014 | 0.1129 | 0.1756 | 0.1756 | 19.0 |
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+ | 1.6137 | 14.0 | 13846 | 1.4914 | 0.2025 | 0.1136 | 0.1766 | 0.1768 | 19.0 |
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+ | 1.6313 | 15.0 | 14835 | 1.4873 | 0.2032 | 0.114 | 0.1769 | 0.1771 | 19.0 |
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+ | 1.6098 | 16.0 | 15824 | 1.4847 | 0.2012 | 0.1133 | 0.175 | 0.1754 | 19.0 |
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+ | 1.6061 | 17.0 | 16813 | 1.4845 | 0.2019 | 0.1138 | 0.1752 | 0.1755 | 19.0 |
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+ | 1.5918 | 18.0 | 17802 | 1.4833 | 0.2011 | 0.1129 | 0.1747 | 0.175 | 19.0 |
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+ | 1.5842 | 19.0 | 18791 | 1.4824 | 0.2013 | 0.1133 | 0.1753 | 0.1755 | 19.0 |
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+ | 1.5964 | 20.0 | 19780 | 1.4825 | 0.201 | 0.1132 | 0.1753 | 0.1755 | 19.0 |
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  ### Framework versions
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  - Transformers 4.31.0
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  - Pytorch 1.13.1.post200
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  - Datasets 2.10.0