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text_shortening_model_v29

Text2Text Generation
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PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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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_v29
    results: []

text_shortening_model_v29

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

  • Loss: 2.6052
  • Rouge1: 0.5112
  • Rouge2: 0.2802
  • Rougel: 0.4539
  • Rougelsum: 0.4538
  • Bert precision: 0.8765
  • Bert recall: 0.8742
  • Average word count: 8.8438
  • Max word count: 16
  • Min word count: 4
  • Average token count: 13.4174
  • % shortened texts with length > 12: 8.7087

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: 8
  • eval_batch_size: 8
  • 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
1.9361 1.0 145 1.4858 0.4996 0.2801 0.4497 0.4507 0.8753 0.8723 8.7808 16 3 13.2372 7.2072
1.4692 2.0 290 1.3868 0.5013 0.2812 0.4477 0.4485 0.8736 0.8731 9.0601 16 3 13.7147 13.2132
1.2301 3.0 435 1.3641 0.5294 0.307 0.4735 0.474 0.8785 0.8799 9.0961 16 4 13.7327 16.8168
1.049 4.0 580 1.3702 0.524 0.2979 0.4705 0.4706 0.8782 0.8788 9.1081 16 4 13.6066 13.8138
0.9261 5.0 725 1.3843 0.5424 0.3166 0.489 0.4886 0.8829 0.8833 8.9219 17 4 13.6907 8.4084
0.8067 6.0 870 1.4039 0.5269 0.3011 0.4682 0.4684 0.8777 0.878 9.2252 17 4 13.973 13.2132
0.7133 7.0 1015 1.5083 0.5168 0.3022 0.4618 0.4613 0.8791 0.8758 8.7447 17 4 13.4655 10.2102
0.6428 8.0 1160 1.4856 0.5184 0.2907 0.4624 0.4617 0.8804 0.8754 8.5976 16 3 13.0571 9.009
0.5741 9.0 1305 1.5332 0.5231 0.3003 0.4669 0.4673 0.8809 0.8791 8.8829 17 4 13.5706 7.5075
0.5231 10.0 1450 1.5603 0.53 0.3032 0.4725 0.4727 0.8843 0.8775 8.4625 17 4 13.033 5.7057
0.4607 11.0 1595 1.6079 0.5118 0.2821 0.4583 0.4577 0.8777 0.8715 8.3453 16 4 13.012 6.9069
0.4136 12.0 1740 1.7147 0.5136 0.2849 0.4558 0.4556 0.8776 0.8734 8.7297 16 3 13.3874 9.3093
0.3829 13.0 1885 1.7425 0.5182 0.287 0.459 0.4591 0.8792 0.8746 8.7207 17 4 13.3934 8.1081
0.3366 14.0 2030 1.7518 0.5171 0.2871 0.4564 0.4557 0.8796 0.8735 8.5195 16 4 13.0811 5.4054
0.3076 15.0 2175 1.8555 0.5139 0.2891 0.4581 0.4581 0.879 0.8754 8.7658 16 4 13.2973 9.9099
0.2908 16.0 2320 1.8983 0.5239 0.3011 0.4654 0.4651 0.8799 0.8794 8.979 16 4 13.6547 12.012
0.2606 17.0 2465 1.9211 0.5158 0.2875 0.4538 0.4542 0.8774 0.8739 8.7868 17 2 13.5736 12.012
0.2477 18.0 2610 1.9208 0.51 0.2872 0.4515 0.4517 0.8774 0.8733 8.6577 17 4 13.3093 10.8108
0.2195 19.0 2755 1.9720 0.5112 0.2838 0.456 0.4559 0.8775 0.8754 8.8799 17 3 13.4835 10.8108
0.1998 20.0 2900 1.9987 0.511 0.2817 0.4526 0.4525 0.8783 0.8751 8.7838 17 3 13.4955 9.9099
0.1936 21.0 3045 2.0389 0.5066 0.2818 0.4482 0.4485 0.8762 0.8722 8.6186 17 4 13.1231 9.009
0.1813 22.0 3190 2.0735 0.5078 0.29 0.4556 0.4562 0.8772 0.8754 8.8198 17 4 13.4895 9.3093
0.1726 23.0 3335 2.0743 0.5108 0.2901 0.458 0.4581 0.8795 0.8736 8.4775 17 2 13.0931 9.009
0.164 24.0 3480 2.1380 0.5077 0.2887 0.4578 0.4565 0.878 0.8727 8.4474 17 4 13.003 5.7057
0.1506 25.0 3625 2.1435 0.5005 0.2725 0.4456 0.4452 0.8748 0.8717 8.6637 17 4 13.2943 6.6066
0.1402 26.0 3770 2.1956 0.5114 0.2899 0.4577 0.4571 0.8769 0.8753 8.8709 17 4 13.3544 9.3093
0.138 27.0 3915 2.2175 0.5079 0.2824 0.4544 0.4548 0.8772 0.8739 8.6847 17 4 13.3423 8.4084
0.1313 28.0 4060 2.2267 0.5048 0.2793 0.4483 0.448 0.8747 0.8717 8.6817 17 4 13.2733 9.009
0.122 29.0 4205 2.2464 0.5105 0.2813 0.4544 0.4548 0.8746 0.8736 8.9099 18 4 13.4595 10.5105
0.1195 30.0 4350 2.2419 0.5124 0.2922 0.461 0.4609 0.8768 0.8733 8.6637 16 4 13.2883 7.5075
0.1131 31.0 4495 2.2243 0.5215 0.3025 0.4702 0.4698 0.8802 0.878 8.7117 16 4 13.3814 9.3093
0.1102 32.0 4640 2.2847 0.5078 0.2826 0.4567 0.4559 0.8788 0.8729 8.3904 18 4 12.9099 6.3063
0.1105 33.0 4785 2.2545 0.5049 0.2759 0.4489 0.4484 0.8762 0.8729 8.6667 18 4 13.1952 9.009
0.099 34.0 4930 2.2819 0.5207 0.296 0.4662 0.4665 0.8814 0.8775 8.6186 17 4 13.1952 8.1081
0.1018 35.0 5075 2.2901 0.5133 0.2812 0.4597 0.4597 0.8777 0.8743 8.7237 17 4 13.3243 10.8108
0.0992 36.0 5220 2.3349 0.5011 0.272 0.4442 0.4439 0.8738 0.8722 8.9129 16 2 13.5856 11.1111
0.0921 37.0 5365 2.3193 0.506 0.2816 0.4539 0.4539 0.8776 0.8739 8.7658 16 4 13.3093 8.7087
0.0936 38.0 5510 2.3404 0.5101 0.2815 0.4565 0.4566 0.8768 0.8754 8.8168 16 4 13.4535 10.5105
0.0833 39.0 5655 2.3583 0.5026 0.2818 0.4512 0.4509 0.8749 0.8743 8.8709 16 3 13.4955 9.3093
0.0869 40.0 5800 2.3443 0.5091 0.2855 0.4521 0.4521 0.8769 0.8743 8.8378 16 4 13.4474 11.4114
0.0783 41.0 5945 2.3609 0.5045 0.2851 0.4519 0.4513 0.8784 0.8738 8.5946 16 4 13.1261 7.8078
0.08 42.0 6090 2.4229 0.5053 0.2774 0.4508 0.4506 0.8769 0.8743 8.6667 16 4 13.2853 8.4084
0.0792 43.0 6235 2.3731 0.5156 0.2877 0.4618 0.4619 0.8775 0.8771 8.955 16 4 13.6937 8.7087
0.075 44.0 6380 2.4058 0.5119 0.286 0.453 0.4535 0.8761 0.8762 8.976 17 3 13.7387 12.012
0.0754 45.0 6525 2.3808 0.5142 0.2894 0.4584 0.4583 0.8772 0.8765 8.967 16 4 13.6096 12.3123
0.0713 46.0 6670 2.3949 0.5093 0.2841 0.4566 0.4568 0.8758 0.8748 8.8559 16 4 13.4775 9.9099
0.066 47.0 6815 2.4103 0.5094 0.2798 0.4551 0.4553 0.8763 0.8753 8.9009 16 4 13.4655 10.2102
0.0684 48.0 6960 2.4284 0.5021 0.2763 0.4476 0.4465 0.8754 0.8733 8.6727 16 4 13.2162 8.7087
0.0656 49.0 7105 2.4512 0.5137 0.289 0.4584 0.4583 0.8763 0.8748 8.8378 16 4 13.4174 9.6096
0.0664 50.0 7250 2.4427 0.5106 0.2789 0.4507 0.4501 0.8761 0.8747 8.7327 16 4 13.5255 8.4084
0.0628 51.0 7395 2.4792 0.5069 0.2802 0.4527 0.453 0.8775 0.8751 8.7417 16 2 13.3063 8.7087
0.0662 52.0 7540 2.4619 0.5103 0.281 0.4567 0.4567 0.8776 0.874 8.6216 16 3 13.1772 9.009
0.0633 53.0 7685 2.4705 0.5053 0.2785 0.4489 0.449 0.8761 0.8735 8.7447 16 4 13.3874 8.7087
0.0592 54.0 7830 2.4978 0.5133 0.2813 0.452 0.4528 0.8769 0.8746 8.8438 16 4 13.4354 9.6096
0.0577 55.0 7975 2.4823 0.5063 0.2793 0.448 0.4488 0.8758 0.8721 8.6036 16 4 13.1111 6.9069
0.0609 56.0 8120 2.4779 0.5133 0.2797 0.4539 0.4544 0.8764 0.8756 8.97 16 3 13.5976 10.5105
0.0539 57.0 8265 2.5132 0.5096 0.2778 0.453 0.4536 0.877 0.8734 8.7117 16 4 13.3003 7.2072
0.0564 58.0 8410 2.4783 0.517 0.2872 0.4622 0.4625 0.8778 0.8759 8.9159 16 4 13.5556 11.4114
0.0543 59.0 8555 2.5184 0.5071 0.2788 0.4515 0.4513 0.8766 0.8734 8.7177 16 4 13.2583 9.009
0.0518 60.0 8700 2.4945 0.5049 0.2754 0.4529 0.4529 0.8755 0.8749 8.9459 16 4 13.6787 10.8108
0.0541 61.0 8845 2.5282 0.4983 0.2693 0.4414 0.4403 0.8723 0.8726 8.973 16 4 13.6667 11.1111
0.0532 62.0 8990 2.5237 0.5007 0.2712 0.4464 0.4456 0.8741 0.8744 9.0541 16 4 13.7477 11.1111
0.0514 63.0 9135 2.5247 0.5041 0.2784 0.4525 0.452 0.8768 0.8735 8.7898 16 4 13.4144 8.7087
0.0516 64.0 9280 2.5289 0.5065 0.2826 0.4517 0.4515 0.8753 0.8745 9.042 16 4 13.6907 11.1111
0.0504 65.0 9425 2.5002 0.5055 0.2826 0.4565 0.4562 0.877 0.8724 8.6727 16 4 13.3123 7.5075
0.0479 66.0 9570 2.5361 0.503 0.2783 0.4529 0.4532 0.8756 0.874 8.8529 16 4 13.4865 8.1081
0.0515 67.0 9715 2.5260 0.5043 0.2758 0.451 0.4512 0.874 0.8748 9.0661 17 4 13.7808 10.5105
0.0544 68.0 9860 2.5213 0.5051 0.2846 0.4543 0.4545 0.8754 0.8739 8.9219 16 3 13.5586 10.5105
0.0445 69.0 10005 2.5543 0.5097 0.2859 0.4573 0.4577 0.878 0.8748 8.6937 16 3 13.3363 9.009
0.0484 70.0 10150 2.5472 0.5028 0.2791 0.4502 0.4503 0.8757 0.8736 8.8078 16 3 13.4264 7.5075
0.0437 71.0 10295 2.5621 0.5089 0.2851 0.4553 0.4556 0.8765 0.8742 8.8408 16 4 13.5105 8.7087
0.0473 72.0 10440 2.5503 0.5087 0.2818 0.4558 0.4555 0.8771 0.8743 8.8559 16 4 13.4204 8.7087
0.0472 73.0 10585 2.5726 0.5168 0.2866 0.4571 0.4577 0.8775 0.8761 8.9039 17 4 13.5285 9.6096
0.041 74.0 10730 2.5982 0.5137 0.2895 0.4594 0.4601 0.8769 0.8757 8.8709 16 4 13.4805 9.3093
0.0409 75.0 10875 2.5589 0.5058 0.2824 0.4553 0.4554 0.8766 0.8746 8.7898 16 4 13.3033 8.7087
0.0441 76.0 11020 2.5642 0.501 0.2791 0.452 0.4521 0.8763 0.8717 8.5225 16 4 13.048 6.006
0.0427 77.0 11165 2.5522 0.5102 0.2864 0.4573 0.4579 0.8784 0.8749 8.7207 17 4 13.3183 7.5075
0.0449 78.0 11310 2.5454 0.5071 0.2846 0.4567 0.4561 0.8775 0.875 8.7658 16 4 13.2523 7.5075
0.0397 79.0 11455 2.5598 0.5111 0.2863 0.4566 0.4569 0.8781 0.8752 8.7267 16 4 13.2973 7.2072
0.046 80.0 11600 2.5171 0.5063 0.2838 0.4541 0.4541 0.8768 0.8734 8.6456 16 4 13.2492 6.6066
0.0403 81.0 11745 2.5398 0.5154 0.2872 0.4584 0.4584 0.8774 0.876 8.9489 18 4 13.4955 8.7087
0.0407 82.0 11890 2.5526 0.5178 0.2904 0.4631 0.4632 0.8789 0.8769 8.8589 18 4 13.4354 7.5075
0.0414 83.0 12035 2.5718 0.5154 0.2876 0.4604 0.4609 0.8783 0.8749 8.7808 17 4 13.3303 7.5075
0.0406 84.0 12180 2.5673 0.5138 0.2861 0.4581 0.4587 0.8773 0.8758 8.8949 17 4 13.4895 8.1081
0.037 85.0 12325 2.5770 0.511 0.2873 0.4575 0.4573 0.8775 0.876 8.8559 16 4 13.4384 8.4084
0.0404 86.0 12470 2.5786 0.5145 0.2848 0.4578 0.4581 0.8774 0.8754 8.8649 16 4 13.4865 8.7087
0.0364 87.0 12615 2.5822 0.5089 0.2791 0.454 0.4539 0.8761 0.8743 8.8288 17 4 13.4174 7.8078
0.0365 88.0 12760 2.5821 0.5105 0.2806 0.4555 0.4559 0.8779 0.8752 8.7838 16 4 13.3634 7.8078
0.0359 89.0 12905 2.5798 0.5121 0.2787 0.4546 0.4549 0.8771 0.8753 8.8799 16 4 13.4835 8.4084
0.0349 90.0 13050 2.5960 0.5109 0.2788 0.4533 0.454 0.8775 0.8747 8.8108 16 4 13.3874 9.009
0.035 91.0 13195 2.5979 0.5072 0.2778 0.454 0.4539 0.8764 0.8743 8.8589 16 4 13.3964 9.6096
0.0355 92.0 13340 2.6016 0.5101 0.2795 0.4544 0.4548 0.8767 0.8743 8.8589 16 4 13.4505 9.009
0.0352 93.0 13485 2.6036 0.5107 0.2814 0.455 0.4554 0.8772 0.8747 8.8619 16 4 13.4294 9.009
0.0338 94.0 13630 2.6016 0.5065 0.2771 0.4512 0.4514 0.8758 0.8741 8.9249 16 4 13.5165 9.3093
0.0359 95.0 13775 2.6044 0.5071 0.2761 0.4496 0.4501 0.8755 0.8733 8.8559 16 4 13.4264 9.6096
0.0349 96.0 13920 2.5986 0.5072 0.277 0.4523 0.4524 0.8756 0.8736 8.8679 16 4 13.4655 9.6096
0.0358 97.0 14065 2.5994 0.5068 0.276 0.4498 0.4502 0.8749 0.8733 8.8589 16 4 13.4685 8.7087
0.0338 98.0 14210 2.6041 0.5105 0.2805 0.4536 0.4535 0.8761 0.8741 8.8498 16 4 13.4444 8.7087
0.0359 99.0 14355 2.6051 0.5095 0.2774 0.452 0.4522 0.876 0.8738 8.8529 16 4 13.4174 9.009
0.0357 100.0 14500 2.6052 0.5112 0.2802 0.4539 0.4538 0.8765 0.8742 8.8438 16 4 13.4174 8.7087

Framework versions

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