--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer model-index: - name: text_shortening_model_v71 results: [] --- # text_shortening_model_v71 This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3875 - Bert precision: 0.9031 - Bert recall: 0.9018 - Bert f1-score: 0.902 - Average word count: 6.4725 - Max word count: 18 - Min word count: 2 - Average token count: 10.5235 - % shortened texts with length > 12: 1.4014 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:| | 1.8083 | 1.0 | 37 | 1.2558 | 0.8866 | 0.8836 | 0.8845 | 6.5606 | 17 | 1 | 10.4024 | 1.4014 | | 1.3282 | 2.0 | 74 | 1.1453 | 0.8901 | 0.8914 | 0.8902 | 6.6797 | 18 | 1 | 10.5205 | 1.9019 | | 1.1679 | 3.0 | 111 | 1.1190 | 0.8937 | 0.8928 | 0.8928 | 6.4825 | 18 | 1 | 10.4174 | 1.8018 | | 1.0406 | 4.0 | 148 | 1.0827 | 0.8927 | 0.8956 | 0.8936 | 6.7377 | 18 | 2 | 10.6837 | 1.6016 | | 0.9626 | 5.0 | 185 | 1.0821 | 0.8969 | 0.8978 | 0.8969 | 6.6176 | 18 | 2 | 10.6476 | 2.002 | | 0.8814 | 6.0 | 222 | 1.0887 | 0.8974 | 0.9004 | 0.8984 | 6.7538 | 18 | 2 | 10.7908 | 2.3023 | | 0.8163 | 7.0 | 259 | 1.0816 | 0.8972 | 0.8979 | 0.8971 | 6.6056 | 18 | 2 | 10.6096 | 1.8018 | | 0.7636 | 8.0 | 296 | 1.0855 | 0.8987 | 0.8999 | 0.8988 | 6.5846 | 18 | 2 | 10.6967 | 2.002 | | 0.7237 | 9.0 | 333 | 1.0949 | 0.8988 | 0.9004 | 0.8992 | 6.6346 | 18 | 2 | 10.6797 | 1.7017 | | 0.6776 | 10.0 | 370 | 1.1174 | 0.9002 | 0.9017 | 0.9005 | 6.6186 | 18 | 2 | 10.6947 | 1.7017 | | 0.6399 | 11.0 | 407 | 1.1237 | 0.8988 | 0.9002 | 0.8991 | 6.6316 | 18 | 2 | 10.6567 | 2.1021 | | 0.5949 | 12.0 | 444 | 1.1426 | 0.8999 | 0.8988 | 0.8989 | 6.4755 | 18 | 2 | 10.5485 | 1.4014 | | 0.5685 | 13.0 | 481 | 1.1564 | 0.9003 | 0.9015 | 0.9004 | 6.6216 | 18 | 2 | 10.6136 | 1.7017 | | 0.5374 | 14.0 | 518 | 1.1690 | 0.9003 | 0.8997 | 0.8995 | 6.5506 | 18 | 2 | 10.5726 | 1.8018 | | 0.5183 | 15.0 | 555 | 1.1736 | 0.9008 | 0.8997 | 0.8998 | 6.5415 | 18 | 2 | 10.5526 | 1.6016 | | 0.4862 | 16.0 | 592 | 1.1882 | 0.8995 | 0.9001 | 0.8994 | 6.5936 | 18 | 2 | 10.6056 | 1.3013 | | 0.4769 | 17.0 | 629 | 1.1910 | 0.9005 | 0.9003 | 0.8999 | 6.5716 | 18 | 2 | 10.6026 | 1.6016 | | 0.4565 | 18.0 | 666 | 1.1957 | 0.9009 | 0.9 | 0.9 | 6.4615 | 18 | 2 | 10.5275 | 1.1011 | | 0.4264 | 19.0 | 703 | 1.2276 | 0.9008 | 0.9004 | 0.9001 | 6.5125 | 18 | 2 | 10.5556 | 1.4014 | | 0.4245 | 20.0 | 740 | 1.2415 | 0.9023 | 0.9005 | 0.9009 | 6.4605 | 18 | 2 | 10.4945 | 1.4014 | | 0.4015 | 21.0 | 777 | 1.2658 | 0.9011 | 0.9004 | 0.9003 | 6.5135 | 18 | 2 | 10.5636 | 1.2012 | | 0.3903 | 22.0 | 814 | 1.2779 | 0.9021 | 0.9018 | 0.9015 | 6.5495 | 18 | 2 | 10.5475 | 1.1011 | | 0.3821 | 23.0 | 851 | 1.2899 | 0.9016 | 0.902 | 0.9014 | 6.5716 | 18 | 2 | 10.6336 | 1.4014 | | 0.3595 | 24.0 | 888 | 1.3062 | 0.9007 | 0.9013 | 0.9005 | 6.5936 | 18 | 2 | 10.6947 | 1.3013 | | 0.3551 | 25.0 | 925 | 1.3088 | 0.9015 | 0.9005 | 0.9006 | 6.4975 | 17 | 2 | 10.5355 | 1.2012 | | 0.343 | 26.0 | 962 | 1.3169 | 0.9018 | 0.9009 | 0.9009 | 6.5005 | 17 | 2 | 10.5716 | 1.2012 | | 0.3426 | 27.0 | 999 | 1.3264 | 0.8997 | 0.9018 | 0.9003 | 6.6486 | 17 | 2 | 10.7658 | 1.4014 | | 0.3314 | 28.0 | 1036 | 1.3234 | 0.9018 | 0.9008 | 0.9008 | 6.4865 | 18 | 2 | 10.5165 | 1.2012 | | 0.3187 | 29.0 | 1073 | 1.3378 | 0.9013 | 0.9003 | 0.9003 | 6.5055 | 18 | 2 | 10.5305 | 1.2012 | | 0.3169 | 30.0 | 1110 | 1.3497 | 0.9015 | 0.9003 | 0.9004 | 6.4835 | 18 | 2 | 10.5546 | 1.2012 | | 0.312 | 31.0 | 1147 | 1.3589 | 0.9018 | 0.8997 | 0.9003 | 6.4585 | 18 | 2 | 10.4615 | 1.2012 | | 0.2995 | 32.0 | 1184 | 1.3572 | 0.901 | 0.9006 | 0.9004 | 6.5215 | 18 | 2 | 10.5866 | 1.3013 | | 0.2987 | 33.0 | 1221 | 1.3647 | 0.9014 | 0.9009 | 0.9007 | 6.5305 | 18 | 2 | 10.5956 | 1.5015 | | 0.2907 | 34.0 | 1258 | 1.3693 | 0.902 | 0.9007 | 0.9009 | 6.4585 | 18 | 2 | 10.5205 | 1.2012 | | 0.2853 | 35.0 | 1295 | 1.3774 | 0.9026 | 0.9016 | 0.9016 | 6.4935 | 18 | 2 | 10.5385 | 1.2012 | | 0.2746 | 36.0 | 1332 | 1.3815 | 0.9027 | 0.9023 | 0.9021 | 6.5285 | 18 | 2 | 10.5706 | 1.4014 | | 0.2798 | 37.0 | 1369 | 1.3818 | 0.9026 | 0.9016 | 0.9016 | 6.4935 | 18 | 2 | 10.5285 | 1.4014 | | 0.2801 | 38.0 | 1406 | 1.3858 | 0.9031 | 0.9018 | 0.902 | 6.4665 | 18 | 2 | 10.5175 | 1.3013 | | 0.2773 | 39.0 | 1443 | 1.3868 | 0.9031 | 0.9018 | 0.902 | 6.4625 | 18 | 2 | 10.5185 | 1.3013 | | 0.2756 | 40.0 | 1480 | 1.3875 | 0.9031 | 0.9018 | 0.902 | 6.4725 | 18 | 2 | 10.5235 | 1.4014 | ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3