--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer metrics: - rouge model-index: - name: text_shortening_model_v7 results: [] --- # text_shortening_model_v7 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: 1.4907 - Rouge1: 0.5855 - Rouge2: 0.3458 - Rougel: 0.525 - Rougelsum: 0.5248 - Bert precision: 0.8932 - Bert recall: 0.9014 - Average word count: 11.6 - Max word count: 18 - Min word count: 6 - Average token count: 16.8 ## 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: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert precision | Bert recall | Average word count | Max word count | Min word count | Average token count | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:| | 2.285 | 1.0 | 8 | 1.8416 | 0.5247 | 0.3056 | 0.4646 | 0.4648 | 0.8769 | 0.8826 | 11.2786 | 18 | 1 | 16.7643 | | 1.9309 | 2.0 | 16 | 1.7082 | 0.5311 | 0.3091 | 0.4698 | 0.4696 | 0.8779 | 0.8859 | 11.6214 | 18 | 4 | 17.1 | | 1.8124 | 3.0 | 24 | 1.6491 | 0.5348 | 0.3068 | 0.4768 | 0.4763 | 0.8845 | 0.8895 | 11.2071 | 18 | 5 | 16.3357 | | 1.714 | 4.0 | 32 | 1.6132 | 0.5496 | 0.3135 | 0.4871 | 0.4856 | 0.8859 | 0.8931 | 11.3143 | 18 | 5 | 16.5429 | | 1.6574 | 5.0 | 40 | 1.5831 | 0.5655 | 0.3305 | 0.5051 | 0.5044 | 0.887 | 0.8993 | 11.8571 | 17 | 5 | 17.2 | | 1.5906 | 6.0 | 48 | 1.5574 | 0.5706 | 0.3303 | 0.5075 | 0.5071 | 0.8856 | 0.902 | 12.2714 | 17 | 6 | 17.7143 | | 1.5538 | 7.0 | 56 | 1.5241 | 0.5745 | 0.3332 | 0.5096 | 0.5094 | 0.8871 | 0.9011 | 12.0429 | 17 | 5 | 17.4 | | 1.4875 | 8.0 | 64 | 1.5150 | 0.5773 | 0.3353 | 0.5117 | 0.512 | 0.8862 | 0.9024 | 12.2 | 17 | 6 | 17.6 | | 1.4466 | 9.0 | 72 | 1.4969 | 0.5781 | 0.3345 | 0.5092 | 0.5096 | 0.8881 | 0.9006 | 12.0643 | 17 | 6 | 17.3429 | | 1.4166 | 10.0 | 80 | 1.4864 | 0.5752 | 0.3326 | 0.5085 | 0.5085 | 0.8887 | 0.8999 | 11.9357 | 17 | 6 | 17.2286 | | 1.3887 | 11.0 | 88 | 1.4809 | 0.5738 | 0.3271 | 0.5049 | 0.5051 | 0.8862 | 0.9001 | 12.1429 | 17 | 6 | 17.4786 | | 1.3321 | 12.0 | 96 | 1.4755 | 0.5811 | 0.337 | 0.5144 | 0.5145 | 0.8879 | 0.9017 | 12.2429 | 17 | 6 | 17.6286 | | 1.3167 | 13.0 | 104 | 1.4635 | 0.5816 | 0.3355 | 0.5143 | 0.5137 | 0.8886 | 0.9015 | 12.15 | 17 | 6 | 17.5214 | | 1.2763 | 14.0 | 112 | 1.4593 | 0.5817 | 0.3345 | 0.5141 | 0.5138 | 0.8882 | 0.9007 | 12.1071 | 17 | 6 | 17.3714 | | 1.2584 | 15.0 | 120 | 1.4640 | 0.5851 | 0.337 | 0.5182 | 0.5181 | 0.8884 | 0.9016 | 12.15 | 17 | 6 | 17.4143 | | 1.2266 | 16.0 | 128 | 1.4652 | 0.5777 | 0.3321 | 0.5124 | 0.5127 | 0.8873 | 0.9 | 12.0571 | 17 | 6 | 17.3071 | | 1.2077 | 17.0 | 136 | 1.4627 | 0.5798 | 0.3326 | 0.5142 | 0.5147 | 0.8876 | 0.9002 | 12.0 | 17 | 6 | 17.2429 | | 1.1881 | 18.0 | 144 | 1.4628 | 0.5784 | 0.3312 | 0.5121 | 0.5126 | 0.8866 | 0.8993 | 12.0429 | 17 | 6 | 17.3071 | | 1.1721 | 19.0 | 152 | 1.4589 | 0.5754 | 0.3284 | 0.5105 | 0.5114 | 0.8874 | 0.8993 | 11.9571 | 17 | 6 | 17.2143 | | 1.1419 | 20.0 | 160 | 1.4561 | 0.5748 | 0.3296 | 0.511 | 0.511 | 0.8873 | 0.8993 | 11.9786 | 17 | 6 | 17.2357 | | 1.1299 | 21.0 | 168 | 1.4605 | 0.5813 | 0.3349 | 0.518 | 0.518 | 0.8876 | 0.9006 | 12.1357 | 18 | 6 | 17.35 | | 1.1295 | 22.0 | 176 | 1.4605 | 0.5756 | 0.3292 | 0.512 | 0.5117 | 0.8874 | 0.8985 | 11.95 | 17 | 6 | 17.1714 | | 1.1091 | 23.0 | 184 | 1.4609 | 0.5746 | 0.3277 | 0.5129 | 0.5129 | 0.8877 | 0.899 | 11.9571 | 17 | 6 | 17.1857 | | 1.0963 | 24.0 | 192 | 1.4616 | 0.5715 | 0.3236 | 0.5101 | 0.5096 | 0.8868 | 0.8987 | 11.9571 | 17 | 6 | 17.25 | | 1.0713 | 25.0 | 200 | 1.4590 | 0.5733 | 0.3264 | 0.5119 | 0.5117 | 0.8872 | 0.8992 | 11.9857 | 17 | 6 | 17.2286 | | 1.0578 | 26.0 | 208 | 1.4569 | 0.577 | 0.3317 | 0.5139 | 0.5141 | 0.8888 | 0.8996 | 11.9071 | 17 | 6 | 17.1143 | | 1.0416 | 27.0 | 216 | 1.4638 | 0.5761 | 0.3312 | 0.5145 | 0.5138 | 0.8883 | 0.8994 | 12.0071 | 18 | 6 | 17.2071 | | 1.0398 | 28.0 | 224 | 1.4657 | 0.5784 | 0.3351 | 0.5149 | 0.515 | 0.8887 | 0.8992 | 11.9 | 18 | 6 | 17.0429 | | 1.0286 | 29.0 | 232 | 1.4684 | 0.5776 | 0.335 | 0.5164 | 0.516 | 0.8889 | 0.8992 | 11.9429 | 18 | 6 | 17.1 | | 1.0095 | 30.0 | 240 | 1.4734 | 0.5772 | 0.3381 | 0.5178 | 0.5177 | 0.8886 | 0.8989 | 11.9143 | 18 | 6 | 17.1214 | | 1.0093 | 31.0 | 248 | 1.4737 | 0.5776 | 0.3374 | 0.5193 | 0.5188 | 0.889 | 0.8998 | 11.8714 | 18 | 6 | 17.1 | | 0.9892 | 32.0 | 256 | 1.4707 | 0.5836 | 0.3469 | 0.5246 | 0.5251 | 0.8902 | 0.9005 | 11.7929 | 18 | 6 | 16.9786 | | 0.9982 | 33.0 | 264 | 1.4734 | 0.5832 | 0.3444 | 0.5249 | 0.5248 | 0.89 | 0.9004 | 11.8571 | 18 | 6 | 17.0929 | | 0.983 | 34.0 | 272 | 1.4767 | 0.5804 | 0.3427 | 0.5224 | 0.5221 | 0.8899 | 0.8997 | 11.7286 | 18 | 6 | 17.0071 | | 0.962 | 35.0 | 280 | 1.4790 | 0.5805 | 0.3402 | 0.5215 | 0.5214 | 0.8901 | 0.8995 | 11.6929 | 18 | 6 | 16.9643 | | 0.9575 | 36.0 | 288 | 1.4817 | 0.5817 | 0.3411 | 0.5209 | 0.5214 | 0.8906 | 0.9001 | 11.6143 | 18 | 6 | 16.8714 | | 0.948 | 37.0 | 296 | 1.4842 | 0.5823 | 0.3421 | 0.522 | 0.5224 | 0.891 | 0.8999 | 11.6429 | 18 | 6 | 16.8714 | | 0.9448 | 38.0 | 304 | 1.4843 | 0.5812 | 0.3426 | 0.5223 | 0.5223 | 0.891 | 0.8999 | 11.5786 | 18 | 6 | 16.8143 | | 0.9415 | 39.0 | 312 | 1.4860 | 0.5802 | 0.3419 | 0.5203 | 0.52 | 0.8909 | 0.8992 | 11.5357 | 18 | 6 | 16.7786 | | 0.9536 | 40.0 | 320 | 1.4868 | 0.5801 | 0.3382 | 0.5198 | 0.5195 | 0.8906 | 0.8982 | 11.5429 | 18 | 6 | 16.7286 | | 0.9249 | 41.0 | 328 | 1.4891 | 0.5804 | 0.3386 | 0.5203 | 0.5201 | 0.8917 | 0.8994 | 11.5929 | 18 | 6 | 16.7857 | | 0.9287 | 42.0 | 336 | 1.4904 | 0.5767 | 0.3397 | 0.5181 | 0.5181 | 0.8906 | 0.8994 | 11.6429 | 18 | 6 | 16.8929 | | 0.94 | 43.0 | 344 | 1.4923 | 0.5824 | 0.3431 | 0.5227 | 0.5227 | 0.8918 | 0.9011 | 11.6429 | 18 | 6 | 16.8929 | | 0.9118 | 44.0 | 352 | 1.4921 | 0.5835 | 0.3442 | 0.5238 | 0.524 | 0.8924 | 0.9013 | 11.6286 | 18 | 6 | 16.8429 | | 0.9343 | 45.0 | 360 | 1.4907 | 0.5824 | 0.3438 | 0.5225 | 0.5228 | 0.8921 | 0.9011 | 11.6286 | 18 | 6 | 16.8571 | | 0.9133 | 46.0 | 368 | 1.4902 | 0.584 | 0.3453 | 0.5236 | 0.5236 | 0.893 | 0.9013 | 11.6 | 18 | 6 | 16.8071 | | 0.9162 | 47.0 | 376 | 1.4903 | 0.584 | 0.3453 | 0.5236 | 0.5236 | 0.8929 | 0.9012 | 11.5929 | 18 | 6 | 16.8071 | | 0.9088 | 48.0 | 384 | 1.4904 | 0.5848 | 0.3454 | 0.5243 | 0.5242 | 0.8931 | 0.9013 | 11.6 | 18 | 6 | 16.8 | | 0.9225 | 49.0 | 392 | 1.4908 | 0.5855 | 0.3458 | 0.525 | 0.5248 | 0.8932 | 0.9014 | 11.6 | 18 | 6 | 16.8 | | 0.9215 | 50.0 | 400 | 1.4907 | 0.5855 | 0.3458 | 0.525 | 0.5248 | 0.8932 | 0.9014 | 11.6 | 18 | 6 | 16.8 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3