--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer model-index: - name: text_shortening_model_v76 results: [] --- # text_shortening_model_v76 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: 1.1244 - Bert precision: 0.8967 - Bert recall: 0.8969 - Bert f1-score: 0.8964 - Average word count: 6.8061 - Max word count: 16 - Min word count: 2 - Average token count: 10.9902 - % shortened texts with length > 12: 1.5951 ## 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: 0.0001 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:| | 1.8741 | 1.0 | 30 | 1.3873 | 0.8846 | 0.8811 | 0.8823 | 6.7558 | 15 | 2 | 10.6282 | 2.5767 | | 1.4617 | 2.0 | 60 | 1.2781 | 0.8879 | 0.8867 | 0.8868 | 6.8613 | 16 | 2 | 10.773 | 0.9816 | | 1.3352 | 3.0 | 90 | 1.2202 | 0.8908 | 0.8894 | 0.8896 | 6.8503 | 14 | 2 | 10.8245 | 0.9816 | | 1.2484 | 4.0 | 120 | 1.1879 | 0.892 | 0.8902 | 0.8907 | 6.7816 | 17 | 1 | 10.7963 | 1.1043 | | 1.1842 | 5.0 | 150 | 1.1657 | 0.893 | 0.8904 | 0.8913 | 6.6945 | 14 | 2 | 10.6822 | 0.6135 | | 1.1263 | 6.0 | 180 | 1.1490 | 0.8932 | 0.8921 | 0.8921 | 6.8601 | 17 | 2 | 10.8663 | 1.7178 | | 1.0859 | 7.0 | 210 | 1.1347 | 0.8909 | 0.8942 | 0.8921 | 7.0663 | 17 | 1 | 11.1975 | 2.3313 | | 1.0511 | 8.0 | 240 | 1.1219 | 0.8925 | 0.8934 | 0.8925 | 6.865 | 17 | 1 | 11.0074 | 1.227 | | 1.0023 | 9.0 | 270 | 1.1118 | 0.8936 | 0.8937 | 0.8931 | 6.8393 | 17 | 1 | 10.9963 | 1.7178 | | 0.9795 | 10.0 | 300 | 1.1073 | 0.8939 | 0.8929 | 0.8929 | 6.7227 | 17 | 1 | 10.8528 | 0.8589 | | 0.9489 | 11.0 | 330 | 1.1050 | 0.8932 | 0.8951 | 0.8937 | 6.9337 | 17 | 2 | 11.0969 | 1.5951 | | 0.9275 | 12.0 | 360 | 1.1026 | 0.8945 | 0.8953 | 0.8945 | 6.8331 | 17 | 2 | 11.0135 | 1.4724 | | 0.8829 | 13.0 | 390 | 1.0989 | 0.8946 | 0.8957 | 0.8947 | 6.8638 | 17 | 1 | 11.038 | 1.3497 | | 0.8762 | 14.0 | 420 | 1.0975 | 0.8939 | 0.8962 | 0.8946 | 6.9239 | 17 | 1 | 11.1423 | 2.0859 | | 0.8559 | 15.0 | 450 | 1.0988 | 0.8953 | 0.8953 | 0.8948 | 6.8049 | 16 | 1 | 10.9742 | 1.7178 | | 0.8347 | 16.0 | 480 | 1.0960 | 0.8963 | 0.8972 | 0.8963 | 6.8233 | 16 | 1 | 11.0258 | 1.4724 | | 0.8166 | 17.0 | 510 | 1.1009 | 0.8973 | 0.8974 | 0.8969 | 6.7914 | 16 | 2 | 11.0135 | 1.227 | | 0.8054 | 18.0 | 540 | 1.1015 | 0.8957 | 0.8972 | 0.896 | 6.8896 | 17 | 1 | 11.0871 | 1.9632 | | 0.786 | 19.0 | 570 | 1.1064 | 0.896 | 0.897 | 0.8961 | 6.8356 | 16 | 2 | 11.038 | 1.7178 | | 0.7764 | 20.0 | 600 | 1.1000 | 0.8964 | 0.8965 | 0.896 | 6.7951 | 16 | 3 | 10.9804 | 1.5951 | | 0.7526 | 21.0 | 630 | 1.1040 | 0.8961 | 0.8976 | 0.8964 | 6.8663 | 17 | 3 | 11.0748 | 1.7178 | | 0.7467 | 22.0 | 660 | 1.1051 | 0.8953 | 0.8964 | 0.8954 | 6.8184 | 16 | 3 | 11.0221 | 1.5951 | | 0.734 | 23.0 | 690 | 1.1057 | 0.8965 | 0.897 | 0.8963 | 6.8307 | 16 | 2 | 11.0049 | 1.5951 | | 0.7268 | 24.0 | 720 | 1.1027 | 0.8956 | 0.8973 | 0.896 | 6.9301 | 17 | 3 | 11.1153 | 1.8405 | | 0.718 | 25.0 | 750 | 1.1062 | 0.8965 | 0.8971 | 0.8963 | 6.8258 | 16 | 2 | 11.016 | 1.5951 | | 0.7068 | 26.0 | 780 | 1.1058 | 0.8961 | 0.8967 | 0.896 | 6.816 | 16 | 2 | 11.0061 | 1.4724 | | 0.6985 | 27.0 | 810 | 1.1120 | 0.8961 | 0.8977 | 0.8965 | 6.8933 | 16 | 2 | 11.1018 | 1.9632 | | 0.6831 | 28.0 | 840 | 1.1130 | 0.8965 | 0.8968 | 0.8962 | 6.8184 | 16 | 2 | 11.0037 | 1.7178 | | 0.6769 | 29.0 | 870 | 1.1144 | 0.8973 | 0.8975 | 0.897 | 6.7779 | 17 | 2 | 10.989 | 1.4724 | | 0.6803 | 30.0 | 900 | 1.1139 | 0.8976 | 0.898 | 0.8974 | 6.8098 | 17 | 2 | 10.9779 | 1.5951 | | 0.6618 | 31.0 | 930 | 1.1147 | 0.8973 | 0.8978 | 0.8971 | 6.8037 | 17 | 2 | 10.9902 | 1.227 | | 0.6745 | 32.0 | 960 | 1.1157 | 0.8962 | 0.897 | 0.8961 | 6.8307 | 16 | 2 | 11.0135 | 1.4724 | | 0.6618 | 33.0 | 990 | 1.1193 | 0.8963 | 0.897 | 0.8962 | 6.8123 | 17 | 2 | 10.9951 | 1.3497 | | 0.6572 | 34.0 | 1020 | 1.1223 | 0.897 | 0.8977 | 0.8969 | 6.8209 | 16 | 2 | 11.0037 | 1.4724 | | 0.6562 | 35.0 | 1050 | 1.1240 | 0.8963 | 0.8971 | 0.8963 | 6.854 | 17 | 2 | 11.0196 | 1.7178 | | 0.6433 | 36.0 | 1080 | 1.1233 | 0.8969 | 0.8967 | 0.8964 | 6.8049 | 16 | 2 | 10.9632 | 1.4724 | | 0.6405 | 37.0 | 1110 | 1.1236 | 0.8974 | 0.8977 | 0.8971 | 6.8245 | 16 | 2 | 11.011 | 1.5951 | | 0.645 | 38.0 | 1140 | 1.1239 | 0.8967 | 0.897 | 0.8964 | 6.8135 | 16 | 2 | 10.9902 | 1.8405 | | 0.6409 | 39.0 | 1170 | 1.1244 | 0.8967 | 0.897 | 0.8964 | 6.8086 | 16 | 2 | 10.9939 | 1.5951 | | 0.6371 | 40.0 | 1200 | 1.1244 | 0.8967 | 0.8969 | 0.8964 | 6.8061 | 16 | 2 | 10.9902 | 1.5951 | ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3