generated_from_trainer

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

text_shortening_model_v73

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Bert precision Bert recall Bert f1-score Average word count Max word count Min word count Average token count % shortened texts with length > 12
1.5857 1.0 37 1.1932 0.8846 0.8848 0.8842 6.5315 16 1 10.4525 1.7017
1.184 2.0 74 1.0965 0.8918 0.8915 0.8911 6.4855 17 2 10.4735 0.5005
1.0114 3.0 111 1.0773 0.8895 0.8962 0.8924 6.8959 18 2 10.995 1.3013
0.8887 4.0 148 1.0798 0.8947 0.8936 0.8937 6.4454 17 2 10.4605 1.8018
0.7851 5.0 185 1.0807 0.8941 0.8948 0.894 6.5676 16 2 10.6016 1.6016
0.7116 6.0 222 1.1002 0.8984 0.8978 0.8976 6.4605 15 2 10.4174 1.2012
0.6472 7.0 259 1.1171 0.8982 0.8997 0.8985 6.5836 16 2 10.6426 1.3013
0.5872 8.0 296 1.1196 0.8998 0.9015 0.9002 6.5415 16 2 10.6226 1.5015
0.5393 9.0 333 1.1739 0.9007 0.8979 0.8988 6.3333 16 2 10.3063 1.1011
0.4879 10.0 370 1.2079 0.8997 0.8983 0.8985 6.3343 15 2 10.2913 1.001
0.4615 11.0 407 1.2230 0.8988 0.8997 0.8988 6.5165 15 2 10.6426 1.3013
0.4245 12.0 444 1.2325 0.8996 0.8979 0.8983 6.3704 15 2 10.4334 1.3013
0.3973 13.0 481 1.2657 0.8973 0.8987 0.8975 6.4855 15 2 10.5876 1.6016
0.3658 14.0 518 1.2875 0.8985 0.8993 0.8984 6.4735 15 2 10.5355 1.2012
0.3422 15.0 555 1.3202 0.9002 0.8991 0.8992 6.2873 14 2 10.3594 1.001
0.3271 16.0 592 1.3315 0.9006 0.9 0.8998 6.3784 15 2 10.4454 0.9009
0.305 17.0 629 1.3441 0.8994 0.9005 0.8995 6.4705 16 2 10.5906 1.2012
0.2847 18.0 666 1.3648 0.8997 0.8989 0.8989 6.3584 14 2 10.4244 0.9009
0.2707 19.0 703 1.3837 0.9005 0.9011 0.9003 6.4545 16 2 10.5365 1.3013
0.254 20.0 740 1.4180 0.8997 0.9006 0.8997 6.4444 15 2 10.5516 1.2012
0.2421 21.0 777 1.4100 0.9014 0.903 0.9017 6.4755 16 2 10.6016 0.9009
0.2301 22.0 814 1.4437 0.9 0.901 0.9 6.4825 15 2 10.5626 0.8008
0.2183 23.0 851 1.4762 0.9003 0.9014 0.9004 6.4995 16 2 10.6116 1.3013
0.2148 24.0 888 1.4815 0.9007 0.9014 0.9006 6.4484 16 2 10.5495 1.1011
0.2013 25.0 925 1.5039 0.9018 0.9015 0.9012 6.4144 15 2 10.4925 1.001
0.1924 26.0 962 1.5217 0.9013 0.9014 0.9009 6.4024 16 2 10.4765 1.2012
0.1854 27.0 999 1.5125 0.902 0.9014 0.9012 6.3774 16 2 10.4565 1.1011
0.1769 28.0 1036 1.5384 0.8998 0.9011 0.9 6.4925 16 2 10.6106 1.001
0.1713 29.0 1073 1.5627 0.9012 0.9018 0.901 6.4715 16 2 10.5395 1.2012
0.1685 30.0 1110 1.5473 0.9011 0.9004 0.9002 6.4064 16 2 10.4484 1.1011
0.1681 31.0 1147 1.5592 0.9018 0.9018 0.9013 6.4194 15 2 10.5165 0.8008
0.1599 32.0 1184 1.5800 0.9006 0.9007 0.9002 6.4254 16 2 10.5005 1.001
0.1509 33.0 1221 1.5822 0.9012 0.9005 0.9004 6.3994 16 2 10.4314 1.001
0.1509 34.0 1258 1.5924 0.9013 0.9008 0.9006 6.4084 16 2 10.4655 1.1011
0.1408 35.0 1295 1.6045 0.9028 0.9024 0.9021 6.4074 16 2 10.4845 1.2012
0.1487 36.0 1332 1.6133 0.9014 0.9012 0.9008 6.4244 16 2 10.4775 1.001
0.1444 37.0 1369 1.6157 0.9016 0.9016 0.9012 6.4304 16 2 10.5045 1.2012
0.1418 38.0 1406 1.6105 0.9012 0.9011 0.9006 6.4084 16 2 10.4615 1.1011
0.1402 39.0 1443 1.6116 0.9017 0.9015 0.9011 6.3894 16 2 10.4494 1.1011
0.1375 40.0 1480 1.6126 0.9015 0.9014 0.901 6.4004 16 2 10.4705 1.1011

Framework versions