metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
model-index:
- name: text_shortening_model_v77
results: []
text_shortening_model_v77
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4183
- Bert precision: 0.8989
- Bert recall: 0.9008
- Bert f1-score: 0.8994
- Average word count: 6.9571
- Max word count: 15
- Min word count: 2
- Average token count: 11.2896
- % shortened texts with length > 12: 2.0859
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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.6557 | 1.0 | 30 | 1.2281 | 0.8905 | 0.8844 | 0.887 | 6.5926 | 15 | 1 | 10.4699 | 1.4724 |
| 1.2524 | 2.0 | 60 | 1.1200 | 0.8933 | 0.8902 | 0.8913 | 6.7227 | 15 | 2 | 10.8294 | 0.9816 |
| 1.1024 | 3.0 | 90 | 1.0914 | 0.8952 | 0.8931 | 0.8937 | 6.7706 | 16 | 2 | 10.811 | 1.1043 |
| 0.9921 | 4.0 | 120 | 1.0805 | 0.8935 | 0.8943 | 0.8935 | 6.9141 | 17 | 2 | 11.0454 | 1.3497 |
| 0.8865 | 5.0 | 150 | 1.1025 | 0.8971 | 0.8949 | 0.8956 | 6.7607 | 16 | 2 | 10.9828 | 1.4724 |
| 0.8273 | 6.0 | 180 | 1.1039 | 0.9005 | 0.8989 | 0.8993 | 6.7583 | 16 | 2 | 10.8982 | 1.9632 |
| 0.7585 | 7.0 | 210 | 1.0975 | 0.8981 | 0.8991 | 0.8982 | 6.9497 | 16 | 3 | 11.135 | 2.2086 |
| 0.7086 | 8.0 | 240 | 1.1068 | 0.8989 | 0.8971 | 0.8976 | 6.7374 | 15 | 2 | 10.9411 | 1.1043 |
| 0.6541 | 9.0 | 270 | 1.1340 | 0.898 | 0.902 | 0.8996 | 7.1239 | 17 | 2 | 11.4258 | 2.8221 |
| 0.6167 | 10.0 | 300 | 1.1316 | 0.8981 | 0.8996 | 0.8984 | 6.962 | 16 | 2 | 11.1436 | 2.6994 |
| 0.5817 | 11.0 | 330 | 1.1507 | 0.8984 | 0.8995 | 0.8985 | 6.9264 | 16 | 2 | 11.2466 | 2.3313 |
| 0.547 | 12.0 | 360 | 1.1416 | 0.899 | 0.8993 | 0.8988 | 6.8601 | 15 | 2 | 11.1865 | 1.5951 |
| 0.5181 | 13.0 | 390 | 1.1775 | 0.8987 | 0.8993 | 0.8986 | 6.8969 | 15 | 3 | 11.1571 | 1.8405 |
| 0.4874 | 14.0 | 420 | 1.2131 | 0.8969 | 0.8999 | 0.8979 | 7.0638 | 16 | 3 | 11.3877 | 2.454 |
| 0.461 | 15.0 | 450 | 1.2263 | 0.9009 | 0.9001 | 0.9001 | 6.8871 | 15 | 2 | 11.1497 | 1.1043 |
| 0.4449 | 16.0 | 480 | 1.2215 | 0.898 | 0.8998 | 0.8984 | 7.0184 | 15 | 2 | 11.3509 | 2.2086 |
| 0.4148 | 17.0 | 510 | 1.2528 | 0.8991 | 0.8997 | 0.899 | 6.8748 | 15 | 2 | 11.1939 | 1.227 |
| 0.3967 | 18.0 | 540 | 1.2512 | 0.8989 | 0.9006 | 0.8994 | 6.9853 | 15 | 2 | 11.3227 | 1.3497 |
| 0.385 | 19.0 | 570 | 1.2683 | 0.898 | 0.8992 | 0.8982 | 6.9755 | 17 | 2 | 11.3227 | 2.454 |
| 0.3667 | 20.0 | 600 | 1.2804 | 0.898 | 0.8982 | 0.8976 | 6.8528 | 15 | 2 | 11.1337 | 1.7178 |
| 0.3579 | 21.0 | 630 | 1.2892 | 0.9006 | 0.899 | 0.8993 | 6.762 | 15 | 2 | 11.0761 | 1.8405 |
| 0.3358 | 22.0 | 660 | 1.3081 | 0.8983 | 0.8996 | 0.8985 | 6.8957 | 15 | 2 | 11.3166 | 1.5951 |
| 0.3261 | 23.0 | 690 | 1.3189 | 0.8988 | 0.8997 | 0.8988 | 6.9571 | 15 | 2 | 11.2491 | 2.6994 |
| 0.3222 | 24.0 | 720 | 1.3116 | 0.8975 | 0.9 | 0.8983 | 7.027 | 15 | 2 | 11.3926 | 2.9448 |
| 0.2977 | 25.0 | 750 | 1.3295 | 0.8988 | 0.9005 | 0.8992 | 6.9755 | 15 | 2 | 11.308 | 1.9632 |
| 0.2977 | 26.0 | 780 | 1.3368 | 0.8972 | 0.9009 | 0.8986 | 7.0442 | 15 | 2 | 11.4184 | 2.5767 |
| 0.2795 | 27.0 | 810 | 1.3515 | 0.9015 | 0.9025 | 0.9015 | 6.9117 | 15 | 2 | 11.2601 | 2.2086 |
| 0.2758 | 28.0 | 840 | 1.3645 | 0.9018 | 0.9013 | 0.9011 | 6.8466 | 15 | 2 | 11.1264 | 1.9632 |
| 0.2696 | 29.0 | 870 | 1.3675 | 0.899 | 0.9002 | 0.8991 | 6.9399 | 15 | 2 | 11.2687 | 1.9632 |
| 0.261 | 30.0 | 900 | 1.3896 | 0.8986 | 0.901 | 0.8993 | 7.0282 | 17 | 2 | 11.3902 | 2.0859 |
| 0.2632 | 31.0 | 930 | 1.3802 | 0.8971 | 0.8988 | 0.8975 | 6.9546 | 15 | 2 | 11.2528 | 2.3313 |
| 0.2488 | 32.0 | 960 | 1.3919 | 0.8998 | 0.9011 | 0.9 | 6.9656 | 15 | 2 | 11.2748 | 2.454 |
| 0.2467 | 33.0 | 990 | 1.3973 | 0.8996 | 0.9013 | 0.9 | 6.9755 | 15 | 2 | 11.3031 | 2.2086 |
| 0.2384 | 34.0 | 1020 | 1.4041 | 0.8988 | 0.9001 | 0.899 | 6.9865 | 15 | 2 | 11.2785 | 2.3313 |
| 0.2369 | 35.0 | 1050 | 1.4044 | 0.8986 | 0.9005 | 0.8991 | 6.9595 | 15 | 2 | 11.2785 | 1.9632 |
| 0.2307 | 36.0 | 1080 | 1.4109 | 0.8985 | 0.9 | 0.8988 | 6.9436 | 15 | 2 | 11.2712 | 2.0859 |
| 0.2285 | 37.0 | 1110 | 1.4118 | 0.8987 | 0.8995 | 0.8987 | 6.9067 | 15 | 2 | 11.2037 | 1.7178 |
| 0.2294 | 38.0 | 1140 | 1.4171 | 0.8992 | 0.9007 | 0.8995 | 6.9436 | 15 | 2 | 11.2712 | 1.9632 |
| 0.2294 | 39.0 | 1170 | 1.4188 | 0.8988 | 0.9008 | 0.8994 | 6.9656 | 15 | 2 | 11.3006 | 2.2086 |
| 0.2261 | 40.0 | 1200 | 1.4183 | 0.8989 | 0.9008 | 0.8994 | 6.9571 | 15 | 2 | 11.2896 | 2.0859 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3