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text_shortening_model_v32

Text2Text Generation
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PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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text_shortening_model_v32 / README.md
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: text_shortening_model_v32
    results: []

text_shortening_model_v32

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.6385
  • Rouge1: 0.527
  • Rouge2: 0.3031
  • Rougel: 0.4768
  • Rougelsum: 0.4774
  • Bert precision: 0.8854
  • Bert recall: 0.8798
  • Average word count: 8.4444
  • Max word count: 17
  • Min word count: 4
  • Average token count: 12.7447
  • % shortened texts with length > 12: 10.2102

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

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 % shortened texts with length > 12
1.2885 1.0 73 1.5384 0.5094 0.2857 0.4536 0.4541 0.8746 0.8764 9.0631 17 3 13.9309 15.015
1.1256 2.0 146 1.4350 0.5228 0.3037 0.4677 0.4684 0.879 0.8771 8.7898 17 4 13.3423 14.1141
1.0169 3.0 219 1.3707 0.5356 0.3171 0.4797 0.4803 0.8806 0.8838 9.1141 17 4 13.7207 14.4144
0.9561 4.0 292 1.3611 0.5449 0.3213 0.4888 0.4896 0.8843 0.8862 8.8408 16 4 13.4865 9.009
0.8725 5.0 365 1.3343 0.5422 0.3199 0.4936 0.4943 0.8847 0.8866 9.0781 16 4 13.6547 11.7117
0.823 6.0 438 1.3632 0.5405 0.3183 0.4913 0.4923 0.8849 0.8824 8.5886 16 4 13.1021 12.9129
0.7673 7.0 511 1.3989 0.5425 0.3181 0.4856 0.4863 0.8815 0.8849 9.2342 16 5 13.7117 15.9159
0.7449 8.0 584 1.4205 0.5391 0.3196 0.4841 0.4845 0.8838 0.8821 8.7207 16 4 13.1201 12.9129
0.7134 9.0 657 1.4581 0.5441 0.3128 0.4884 0.4888 0.8853 0.885 8.6937 16 4 13.2913 7.8078
0.6875 10.0 730 1.4754 0.5434 0.3148 0.4886 0.4884 0.8865 0.8838 8.6727 16 3 13.1081 10.5105
0.6786 11.0 803 1.4771 0.5411 0.3107 0.4891 0.4895 0.8874 0.8836 8.5435 16 4 13.03 8.4084
0.6388 12.0 876 1.5743 0.5379 0.309 0.482 0.4829 0.8851 0.8807 8.5495 15 4 13.033 10.8108
0.6202 13.0 949 1.6033 0.5423 0.3078 0.4852 0.4858 0.8875 0.8834 8.4414 16 2 12.982 9.009
0.6046 14.0 1022 1.6242 0.5352 0.3073 0.4793 0.4795 0.8851 0.8812 8.5165 16 2 12.994 9.9099
0.6019 15.0 1095 1.6496 0.539 0.3001 0.4802 0.4805 0.8861 0.8832 8.7748 16 4 13.1111 9.9099
0.5717 16.0 1168 1.7001 0.5471 0.3198 0.4947 0.4954 0.8876 0.8869 8.8498 17 4 13.3153 14.4144
0.5567 17.0 1241 1.7371 0.5304 0.3012 0.4802 0.4805 0.8849 0.8809 8.4955 16 2 12.8919 9.9099
0.5458 18.0 1314 1.7639 0.5312 0.299 0.4782 0.4784 0.8858 0.8812 8.5045 15 4 13.012 9.009
0.528 19.0 1387 1.8120 0.5282 0.306 0.4791 0.4794 0.8857 0.8819 8.5886 16 3 12.9009 10.8108
0.5055 20.0 1460 1.8516 0.5357 0.3088 0.4793 0.4796 0.8863 0.8821 8.6366 16 4 13.1141 9.3093
0.5098 21.0 1533 1.8717 0.5304 0.2966 0.4746 0.4745 0.8843 0.8806 8.5946 16 4 13.039 9.9099
0.5143 22.0 1606 1.9507 0.533 0.3006 0.4813 0.4819 0.8855 0.8815 8.4895 18 2 12.967 8.4084
0.4923 23.0 1679 1.9452 0.5263 0.2936 0.4748 0.474 0.8845 0.8805 8.4985 16 2 12.9309 9.009
0.4891 24.0 1752 1.9700 0.5306 0.3027 0.48 0.4803 0.8862 0.881 8.4565 15 4 12.982 7.2072
0.4902 25.0 1825 2.0222 0.5336 0.3079 0.4833 0.4836 0.8867 0.8826 8.5465 16 4 12.9429 10.2102
0.4691 26.0 1898 2.0300 0.5332 0.3083 0.4831 0.4838 0.8862 0.8829 8.6036 15 4 13.1231 12.3123
0.4554 27.0 1971 2.0376 0.5345 0.3074 0.4802 0.4802 0.8877 0.8822 8.4354 16 4 12.8018 7.2072
0.4668 28.0 2044 2.0778 0.534 0.3056 0.4836 0.4839 0.8852 0.8816 8.5946 18 4 13.0691 10.5105
0.4637 29.0 2117 2.0837 0.5255 0.2986 0.4761 0.4769 0.8839 0.881 8.5105 16 4 13.048 9.6096
0.4568 30.0 2190 2.1224 0.5332 0.3045 0.4805 0.4801 0.8842 0.8833 8.8198 18 4 13.3483 13.8138
0.4602 31.0 2263 2.1452 0.5323 0.3019 0.4776 0.4775 0.8842 0.882 8.6637 18 4 13.1682 11.7117
0.4584 32.0 2336 2.1395 0.5379 0.3125 0.4873 0.4875 0.8839 0.883 8.7808 15 4 13.3754 10.8108
0.4495 33.0 2409 2.1839 0.5295 0.3002 0.4767 0.4763 0.882 0.8819 8.8979 17 4 13.4685 13.5135
0.4418 34.0 2482 2.2072 0.5266 0.3009 0.477 0.4769 0.8836 0.8791 8.5375 15 2 12.9459 10.5105
0.4378 35.0 2555 2.2251 0.5242 0.2946 0.4728 0.4729 0.883 0.8784 8.5255 17 4 12.8709 10.8108
0.4224 36.0 2628 2.2447 0.5296 0.3023 0.4774 0.4785 0.8843 0.88 8.5736 15 4 12.979 10.8108
0.4322 37.0 2701 2.2509 0.5187 0.2921 0.4694 0.4698 0.8824 0.877 8.4535 15 4 12.8949 12.3123
0.4367 38.0 2774 2.2949 0.5166 0.2887 0.4646 0.4653 0.8807 0.876 8.5465 17 4 12.9369 12.012
0.4301 39.0 2847 2.2866 0.5256 0.298 0.4693 0.4696 0.8825 0.8777 8.5255 16 4 13.0 9.9099
0.4219 40.0 2920 2.2993 0.5213 0.2908 0.4697 0.4699 0.8833 0.8788 8.5646 15 4 13.03 10.5105
0.4165 41.0 2993 2.3157 0.5226 0.2977 0.4697 0.4695 0.884 0.878 8.3964 15 4 12.7988 9.9099
0.4352 42.0 3066 2.3181 0.5199 0.2854 0.4641 0.4641 0.8822 0.8769 8.4925 17 4 12.7958 10.5105
0.4209 43.0 3139 2.3455 0.5247 0.2943 0.4743 0.4746 0.8833 0.8812 8.6757 17 4 13.1111 11.1111
0.4227 44.0 3212 2.3553 0.5146 0.2885 0.4631 0.4638 0.883 0.8765 8.3213 17 4 12.5736 9.9099
0.4205 45.0 3285 2.3684 0.5205 0.2925 0.4652 0.4658 0.8821 0.8779 8.4895 15 4 12.952 11.4114
0.4039 46.0 3358 2.3505 0.5254 0.3 0.4741 0.4742 0.8835 0.8792 8.5105 17 4 12.9339 10.5105
0.41 47.0 3431 2.3901 0.522 0.2994 0.4712 0.4718 0.8829 0.8792 8.5195 16 4 12.9339 11.1111
0.4104 48.0 3504 2.4093 0.5263 0.3 0.473 0.4736 0.8856 0.8791 8.3243 17 4 12.7207 9.009
0.412 49.0 3577 2.4144 0.523 0.2983 0.4702 0.4703 0.8828 0.8804 8.7688 17 4 13.1982 11.7117
0.4165 50.0 3650 2.4154 0.5206 0.2966 0.468 0.4679 0.8836 0.8798 8.6607 17 4 13.048 9.3093
0.4019 51.0 3723 2.4539 0.5242 0.3013 0.474 0.4751 0.8845 0.8806 8.6096 17 3 12.988 11.1111
0.3948 52.0 3796 2.4132 0.5267 0.2984 0.4741 0.4749 0.8834 0.8802 8.6847 17 3 13.1592 13.2132
0.4105 53.0 3869 2.4407 0.5214 0.2937 0.4676 0.4682 0.882 0.8799 8.7117 17 4 13.0901 12.9129
0.4115 54.0 3942 2.4676 0.5292 0.3007 0.4783 0.479 0.8865 0.8797 8.3243 17 3 12.6667 8.4084
0.3972 55.0 4015 2.4592 0.5273 0.3041 0.4777 0.4784 0.8864 0.8799 8.3784 17 3 12.7778 10.8108
0.3965 56.0 4088 2.4719 0.5157 0.293 0.4657 0.4656 0.8829 0.8777 8.4084 17 3 12.7598 10.2102
0.4106 57.0 4161 2.4792 0.52 0.2942 0.4685 0.4692 0.8839 0.8797 8.5165 17 4 12.9309 9.9099
0.3923 58.0 4234 2.5007 0.5229 0.2991 0.4733 0.4738 0.8852 0.88 8.5345 18 4 12.8739 11.4114
0.4065 59.0 4307 2.4745 0.5201 0.2921 0.4686 0.4693 0.8829 0.8788 8.5826 17 4 13.006 10.2102
0.4095 60.0 4380 2.4775 0.5187 0.2925 0.4683 0.4685 0.8826 0.8804 8.6817 15 4 13.1141 10.8108
0.4016 61.0 4453 2.4853 0.5178 0.2897 0.467 0.4675 0.8823 0.8786 8.5766 15 4 13.003 10.8108
0.4015 62.0 4526 2.4844 0.5255 0.2908 0.4704 0.4713 0.8839 0.8799 8.5616 16 4 13.03 9.6096
0.399 63.0 4599 2.5017 0.52 0.2909 0.4669 0.4674 0.8835 0.8793 8.5405 16 4 12.9159 9.009
0.4075 64.0 4672 2.5025 0.523 0.2976 0.4734 0.4741 0.885 0.88 8.5015 17 4 12.8709 9.9099
0.3977 65.0 4745 2.5306 0.5213 0.3006 0.4743 0.4747 0.8842 0.8799 8.4745 17 4 12.9279 10.5105
0.3978 66.0 4818 2.5439 0.5219 0.2982 0.4719 0.472 0.8842 0.8792 8.4414 17 4 12.7357 9.9099
0.3971 67.0 4891 2.5319 0.5293 0.2998 0.4762 0.4769 0.8856 0.8811 8.6156 17 4 12.9309 9.3093
0.3881 68.0 4964 2.5460 0.5216 0.2947 0.4714 0.4715 0.8848 0.879 8.3453 17 4 12.6847 8.4084
0.3947 69.0 5037 2.5447 0.527 0.2998 0.4741 0.4745 0.8844 0.8812 8.5856 17 4 13.015 10.8108
0.3862 70.0 5110 2.5670 0.5271 0.304 0.4766 0.4775 0.885 0.8811 8.5556 17 4 12.9249 9.9099
0.3947 71.0 5183 2.5535 0.5224 0.2984 0.4701 0.4703 0.8844 0.8795 8.5075 17 4 12.8559 10.8108
0.4056 72.0 5256 2.5729 0.5266 0.2987 0.4727 0.4737 0.8837 0.8812 8.6306 17 4 13.0601 11.1111
0.3906 73.0 5329 2.5667 0.5231 0.2982 0.4691 0.4699 0.8828 0.8802 8.6036 17 4 13.0571 10.2102
0.3875 74.0 5402 2.5688 0.5252 0.2972 0.4697 0.4709 0.8836 0.8804 8.5946 17 4 12.994 10.2102
0.3869 75.0 5475 2.5824 0.5283 0.3009 0.4741 0.4743 0.885 0.8823 8.6306 17 4 13.03 11.1111
0.3797 76.0 5548 2.5827 0.5242 0.2992 0.4717 0.4723 0.8838 0.882 8.6697 17 4 13.1021 11.4114
0.3716 77.0 5621 2.5992 0.5197 0.2971 0.4667 0.4681 0.8833 0.8803 8.5766 17 4 12.973 11.7117
0.3852 78.0 5694 2.5840 0.5226 0.3008 0.4703 0.4711 0.8839 0.8803 8.5616 17 3 12.979 11.1111
0.4031 79.0 5767 2.5853 0.5328 0.3096 0.4794 0.4798 0.887 0.882 8.4865 17 3 12.8679 8.7087
0.3849 80.0 5840 2.5943 0.5315 0.3101 0.4811 0.4818 0.8863 0.882 8.4925 17 3 12.8979 8.7087
0.3937 81.0 5913 2.5984 0.5278 0.3033 0.4763 0.4766 0.8851 0.8813 8.5646 17 3 12.9189 9.9099
0.402 82.0 5986 2.6003 0.5229 0.2993 0.4709 0.4717 0.8841 0.8793 8.5135 17 3 12.8889 10.5105
0.4004 83.0 6059 2.6012 0.5261 0.3025 0.4751 0.4756 0.8849 0.8805 8.4835 17 3 12.8138 11.1111
0.3968 84.0 6132 2.6119 0.5266 0.3042 0.4755 0.476 0.8858 0.8811 8.4835 17 3 12.8198 10.5105
0.393 85.0 6205 2.6203 0.5269 0.3026 0.4736 0.4745 0.8856 0.8811 8.5045 17 4 12.8228 10.5105
0.4003 86.0 6278 2.6245 0.5281 0.3035 0.4741 0.4752 0.8856 0.8808 8.4474 17 4 12.7598 9.9099
0.3923 87.0 6351 2.6331 0.5238 0.2992 0.4726 0.4729 0.8848 0.8799 8.4114 17 4 12.7658 9.9099
0.3958 88.0 6424 2.6281 0.5265 0.3015 0.4747 0.4751 0.8848 0.8806 8.4925 17 4 12.8258 10.5105
0.3938 89.0 6497 2.6312 0.5261 0.3034 0.4753 0.4759 0.8848 0.8805 8.4715 17 4 12.8348 10.8108
0.3698 90.0 6570 2.6221 0.5253 0.3018 0.4734 0.4744 0.8845 0.8803 8.4775 17 4 12.8228 10.5105
0.3946 91.0 6643 2.6173 0.5258 0.3025 0.4739 0.4748 0.8849 0.8806 8.4625 17 4 12.8378 10.2102
0.3933 92.0 6716 2.6259 0.5269 0.302 0.476 0.4764 0.8851 0.88 8.4444 17 4 12.7928 10.5105
0.3915 93.0 6789 2.6323 0.5314 0.306 0.4783 0.4789 0.8858 0.8814 8.5195 17 4 12.8739 11.1111
0.3936 94.0 6862 2.6365 0.5293 0.3039 0.4778 0.4785 0.8857 0.8807 8.4775 17 4 12.8048 10.5105
0.3853 95.0 6935 2.6385 0.5294 0.3042 0.4783 0.4788 0.8857 0.8808 8.4835 17 4 12.8198 10.5105
0.3871 96.0 7008 2.6379 0.5283 0.3059 0.4778 0.4786 0.8858 0.8806 8.4865 17 4 12.8198 9.6096
0.3769 97.0 7081 2.6410 0.5283 0.3057 0.4784 0.479 0.8857 0.8806 8.5015 17 4 12.8228 10.2102
0.3997 98.0 7154 2.6420 0.5279 0.3048 0.4777 0.4784 0.8852 0.8801 8.4655 17 4 12.7928 10.2102
0.3935 99.0 7227 2.6392 0.5267 0.3033 0.4763 0.4771 0.8852 0.8799 8.4444 17 4 12.7568 10.2102
0.3891 100.0 7300 2.6385 0.527 0.3031 0.4768 0.4774 0.8854 0.8798 8.4444 17 4 12.7447 10.2102

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3