generated_from_trainer

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text_shortening_model_v72

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
1.6981 1.0 37 1.2099 0.8879 0.8868 0.8868 6.5786 15 1 10.3994 0.8008
1.1993 2.0 74 1.1320 0.8939 0.89 0.8914 6.3013 16 2 10.2663 0.9009
1.0205 3.0 111 1.1073 0.8929 0.8931 0.8925 6.6507 16 2 10.7057 1.6016
0.8912 4.0 148 1.0787 0.8967 0.8966 0.8962 6.5896 16 2 10.5926 1.6016
0.8027 5.0 185 1.1123 0.8991 0.8959 0.897 6.3994 16 2 10.4164 1.1011
0.7251 6.0 222 1.1148 0.8983 0.8941 0.8957 6.3013 16 2 10.3333 1.3013
0.6534 7.0 259 1.1348 0.8993 0.8931 0.8957 6.2332 16 2 10.2012 1.2012
0.5895 8.0 296 1.1537 0.8982 0.8959 0.8966 6.4945 16 2 10.4995 1.6016
0.5483 9.0 333 1.1656 0.901 0.8978 0.899 6.4184 16 2 10.4505 1.7017
0.5117 10.0 370 1.1919 0.8977 0.896 0.8964 6.4565 15 2 10.5696 1.1011
0.4639 11.0 407 1.2106 0.8999 0.8956 0.8973 6.2653 15 2 10.2943 1.001
0.4267 12.0 444 1.2419 0.8975 0.8958 0.8962 6.4625 17 2 10.5115 1.7017
0.4069 13.0 481 1.2583 0.9023 0.8964 0.8988 6.1812 15 2 10.1942 0.9009
0.3775 14.0 518 1.2887 0.8991 0.8982 0.8982 6.4384 15 2 10.5676 1.5015
0.3495 15.0 555 1.3282 0.9015 0.8984 0.8995 6.3604 15 2 10.4895 0.9009
0.3281 16.0 592 1.3276 0.9012 0.8973 0.8988 6.2753 15 2 10.3413 0.5005
0.3083 17.0 629 1.3539 0.9007 0.8979 0.8989 6.3504 16 2 10.3874 1.6016
0.2906 18.0 666 1.3720 0.9006 0.8986 0.8992 6.4204 14 2 10.4785 1.2012
0.2793 19.0 703 1.4130 0.8997 0.8986 0.8987 6.4374 16 2 10.5345 1.5015
0.2656 20.0 740 1.4376 0.9026 0.8986 0.9002 6.2843 16 2 10.3834 1.2012
0.2399 21.0 777 1.4429 0.901 0.8997 0.8999 6.4545 16 2 10.5516 1.5015
0.2316 22.0 814 1.4807 0.899 0.8987 0.8983 6.4975 16 2 10.6667 1.3013
0.2237 23.0 851 1.4941 0.9002 0.8974 0.8983 6.3363 15 2 10.4484 0.9009
0.2079 24.0 888 1.5101 0.9011 0.8982 0.8992 6.3443 16 2 10.4104 1.2012
0.2007 25.0 925 1.5176 0.8991 0.8983 0.8982 6.5065 16 2 10.6216 1.001
0.1952 26.0 962 1.5253 0.9005 0.8979 0.8987 6.3934 15 2 10.4835 1.1011
0.1901 27.0 999 1.5440 0.9007 0.8985 0.8991 6.3904 16 2 10.5185 0.8008
0.1838 28.0 1036 1.5540 0.9008 0.9002 0.9 6.4985 16 2 10.6176 1.3013
0.1773 29.0 1073 1.5576 0.9013 0.9001 0.9003 6.4835 16 2 10.5866 1.3013
0.1692 30.0 1110 1.5746 0.9012 0.9003 0.9003 6.4895 16 2 10.6176 1.5015
0.163 31.0 1147 1.5844 0.9014 0.9 0.9002 6.4655 16 2 10.5756 1.3013
0.1587 32.0 1184 1.6071 0.9008 0.8997 0.8998 6.4615 16 2 10.6076 0.9009
0.156 33.0 1221 1.6166 0.9006 0.8998 0.8997 6.4945 16 2 10.6166 1.2012
0.1546 34.0 1258 1.6099 0.9011 0.8987 0.8994 6.3834 13 2 10.4965 0.9009
0.1472 35.0 1295 1.6167 0.9018 0.8992 0.9001 6.3974 14 2 10.4665 1.001
0.1472 36.0 1332 1.6271 0.9006 0.9 0.8998 6.5185 16 2 10.6216 1.5015
0.1452 37.0 1369 1.6226 0.9023 0.9007 0.901 6.4595 16 2 10.5485 1.4014
0.1415 38.0 1406 1.6221 0.9015 0.9006 0.9006 6.5005 16 2 10.5846 1.4014
0.1398 39.0 1443 1.6272 0.9012 0.9002 0.9003 6.5025 16 2 10.5866 1.2012
0.14 40.0 1480 1.6295 0.9015 0.9003 0.9004 6.4845 16 2 10.5656 1.1011

Framework versions