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text_shortening_model_v28

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_v28
    results: []

text_shortening_model_v28

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

  • Loss: 2.9239
  • Rouge1: 0.4821
  • Rouge2: 0.2554
  • Rougel: 0.4273
  • Rougelsum: 0.4271
  • Bert precision: 0.8753
  • Bert recall: 0.8686
  • Average word count: 8.1231
  • Max word count: 14
  • Min word count: 4
  • Average token count: 12.4805
  • % shortened texts with length > 12: 2.7027

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: 0.005
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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
2.1941 1.0 37 1.6111 0.5035 0.2708 0.4544 0.4553 0.8744 0.8772 9.2643 18 3 13.5826 12.9129
1.4552 2.0 74 1.5748 0.4724 0.2457 0.4313 0.4313 0.8737 0.8635 8.009 17 3 12.024 6.006
1.096 3.0 111 1.5283 0.5016 0.282 0.4515 0.4519 0.8774 0.8757 8.7748 16 4 13.0811 7.2072
0.8801 4.0 148 1.5903 0.4848 0.2549 0.4372 0.4375 0.88 0.8713 8.3544 16 4 12.6607 6.9069
0.7226 5.0 185 1.6953 0.4557 0.2378 0.408 0.4086 0.8752 0.8603 7.3904 13 1 11.6697 0.9009
0.6003 6.0 222 1.8416 0.4935 0.2616 0.4327 0.4339 0.8758 0.8712 8.5736 17 3 12.8498 8.7087
0.4852 7.0 259 1.8375 0.4662 0.2428 0.4147 0.4161 0.8703 0.8653 8.3904 16 2 12.7147 7.5075
0.4469 8.0 296 1.9116 0.4617 0.2433 0.41 0.4117 0.8724 0.8649 8.0781 17 2 12.5495 2.7027
0.4025 9.0 333 1.9871 0.4716 0.2443 0.4161 0.4164 0.8691 0.8662 9.006 19 4 13.4204 15.3153
0.3568 10.0 370 2.0547 0.4864 0.2649 0.4377 0.4377 0.8742 0.8724 8.6396 16 3 13.1381 7.8078
0.3071 11.0 407 2.1554 0.4582 0.2388 0.405 0.4053 0.8712 0.8595 7.7087 14 4 12.033 2.1021
0.2794 12.0 444 2.1352 0.4768 0.2567 0.4341 0.4344 0.8757 0.8705 8.4655 16 4 12.8949 8.1081
0.2627 13.0 481 2.1300 0.4703 0.2518 0.4227 0.4227 0.876 0.8674 8.015 17 3 12.2342 4.5045
0.2251 14.0 518 2.2319 0.4887 0.2623 0.4335 0.4336 0.8757 0.8704 8.3544 15 4 12.7357 5.7057
0.217 15.0 555 2.2311 0.4709 0.2523 0.4196 0.4196 0.8739 0.8683 8.2613 17 4 12.6276 5.4054
0.2097 16.0 592 2.2460 0.471 0.2463 0.4137 0.4147 0.8732 0.8649 8.1682 15 3 12.4384 4.5045
0.1841 17.0 629 2.3917 0.4564 0.229 0.4072 0.4076 0.8709 0.8663 8.3934 16 3 12.7027 5.4054
0.176 18.0 666 2.3731 0.4644 0.2408 0.4093 0.4103 0.87 0.8633 8.1712 16 4 12.5495 4.5045
0.1531 19.0 703 2.3836 0.4925 0.2727 0.439 0.439 0.879 0.8711 8.1111 16 3 12.2703 3.9039
0.1599 20.0 740 2.3611 0.4731 0.2575 0.4199 0.4202 0.8743 0.8669 8.1141 16 3 12.5315 4.8048
0.1469 21.0 777 2.4164 0.4774 0.2515 0.4295 0.4302 0.876 0.8709 8.3754 15 3 12.8348 6.3063
0.1449 22.0 814 2.4769 0.4702 0.2461 0.4205 0.421 0.874 0.8688 8.4054 16 4 12.7508 7.8078
0.1417 23.0 851 2.5470 0.4669 0.2438 0.4163 0.4163 0.8733 0.8649 7.9339 14 3 12.1922 2.7027
0.1255 24.0 888 2.5590 0.4642 0.2379 0.4127 0.4136 0.8736 0.8621 7.6517 14 4 11.7057 2.1021
0.1281 25.0 925 2.4347 0.4707 0.2571 0.4227 0.4233 0.8734 0.8675 8.2492 15 3 12.6937 4.5045
0.1399 26.0 962 2.5391 0.4649 0.2454 0.4132 0.414 0.8703 0.8684 8.6547 17 4 13.1982 8.4084
0.1279 27.0 999 2.5712 0.4723 0.2526 0.4208 0.4207 0.8729 0.8682 8.3393 17 4 12.6547 6.3063
0.1224 28.0 1036 2.5410 0.466 0.2485 0.4159 0.4156 0.8743 0.8663 7.955 15 3 12.2643 3.3033
0.1095 29.0 1073 2.6742 0.4647 0.2382 0.4094 0.4098 0.873 0.8641 8.033 16 4 12.3243 5.1051
0.1202 30.0 1110 2.5533 0.4748 0.2495 0.4225 0.4234 0.8757 0.8676 8.1562 16 4 12.4204 4.8048
0.1236 31.0 1147 2.5441 0.4709 0.2444 0.418 0.4187 0.87 0.8659 8.4144 17 4 12.8228 5.7057
0.1074 32.0 1184 2.6271 0.4845 0.2619 0.4291 0.4301 0.8758 0.8684 8.1502 15 3 12.4985 4.5045
0.0939 33.0 1221 2.6391 0.4806 0.2549 0.4251 0.4261 0.8722 0.869 8.6486 16 3 13.1592 7.8078
0.0976 34.0 1258 2.6159 0.4798 0.2582 0.4264 0.4268 0.8738 0.8701 8.6096 17 3 13.0931 8.4084
0.1042 35.0 1295 2.6224 0.4849 0.2557 0.428 0.4284 0.876 0.8705 8.2673 16 3 12.6757 4.5045
0.094 36.0 1332 2.5925 0.4742 0.2542 0.4289 0.4296 0.8754 0.8683 8.033 15 3 12.3483 3.6036
0.0794 37.0 1369 2.5782 0.4897 0.262 0.4354 0.4364 0.8762 0.8723 8.3153 16 3 12.7538 6.9069
0.0823 38.0 1406 2.6590 0.4752 0.2486 0.4222 0.423 0.8737 0.8651 8.027 15 3 12.3123 6.3063
0.0813 39.0 1443 2.6823 0.4817 0.2605 0.427 0.4276 0.8763 0.8696 8.1532 15 2 12.6006 5.1051
0.0868 40.0 1480 2.6642 0.4827 0.2572 0.4308 0.4314 0.8757 0.8702 8.3964 16 3 12.6877 8.1081
0.0786 41.0 1517 2.7908 0.4623 0.24 0.4086 0.4096 0.8704 0.863 8.1351 16 4 12.7447 7.2072
0.0901 42.0 1554 2.7242 0.4613 0.2405 0.4115 0.413 0.8716 0.8636 8.2523 18 4 12.5465 6.9069
0.0912 43.0 1591 2.7376 0.474 0.2446 0.4194 0.4191 0.8707 0.8694 8.6877 16 3 13.2282 10.5105
0.0887 44.0 1628 2.7192 0.479 0.2539 0.4266 0.4268 0.874 0.8703 8.4865 15 4 13.1321 7.2072
0.0807 45.0 1665 2.6935 0.4738 0.2501 0.4213 0.4223 0.874 0.8675 8.2042 16 2 12.6787 6.006
0.0801 46.0 1702 2.7149 0.4662 0.2443 0.4229 0.4236 0.8745 0.8659 8.033 15 3 12.3453 4.2042
0.0764 47.0 1739 2.6544 0.4697 0.249 0.4206 0.4202 0.8726 0.8668 8.2432 16 4 12.6637 6.9069
0.0765 48.0 1776 2.7157 0.4764 0.2535 0.4234 0.4236 0.8762 0.8676 8.021 15 3 12.3544 4.5045
0.065 49.0 1813 2.8051 0.4666 0.2452 0.4161 0.4165 0.8728 0.8665 8.2673 16 2 12.6246 5.1051
0.0626 50.0 1850 2.7845 0.4781 0.2519 0.4254 0.4253 0.8746 0.8688 8.2192 16 3 12.5796 5.4054
0.0608 51.0 1887 2.7371 0.4745 0.2456 0.4213 0.4208 0.8751 0.866 8.0871 17 2 12.3063 6.9069
0.0599 52.0 1924 2.7620 0.474 0.2515 0.419 0.4204 0.8718 0.8667 8.1381 15 4 12.8979 3.9039
0.0625 53.0 1961 2.8097 0.4646 0.2481 0.4137 0.4146 0.8706 0.8663 8.2733 15 3 12.7237 4.5045
0.0529 54.0 1998 2.8677 0.4714 0.2436 0.4142 0.4147 0.8745 0.8651 7.8709 16 2 12.2012 4.2042
0.05 55.0 2035 2.7892 0.467 0.2465 0.4152 0.4159 0.8739 0.8668 8.1712 17 2 12.4925 3.3033
0.047 56.0 2072 2.7682 0.4719 0.2451 0.4223 0.423 0.8717 0.866 8.1802 15 3 12.5826 5.1051
0.0504 57.0 2109 2.7897 0.4823 0.2555 0.427 0.4276 0.8754 0.8717 8.5345 15 3 12.9249 7.5075
0.0463 58.0 2146 2.8505 0.471 0.2513 0.42 0.4204 0.8748 0.8683 8.2132 15 3 12.6426 5.7057
0.0487 59.0 2183 2.7699 0.4658 0.2472 0.4156 0.4166 0.8726 0.8667 8.1231 15 3 12.5465 3.9039
0.045 60.0 2220 2.7589 0.4718 0.2495 0.4211 0.4216 0.8741 0.8676 8.2432 17 4 12.5556 5.1051
0.047 61.0 2257 2.8092 0.4814 0.2517 0.4253 0.4257 0.8759 0.8687 7.997 17 3 12.3393 3.003
0.0415 62.0 2294 2.8059 0.4689 0.2494 0.4183 0.4191 0.8767 0.8655 7.7538 17 2 12.1381 2.4024
0.0429 63.0 2331 2.8317 0.4783 0.2516 0.4248 0.4252 0.8764 0.8689 8.0811 17 3 12.4234 3.003
0.0383 64.0 2368 2.8147 0.4728 0.2547 0.4189 0.4193 0.8732 0.867 8.1622 18 3 12.5916 4.2042
0.039 65.0 2405 2.8237 0.4638 0.2401 0.414 0.4145 0.871 0.8654 8.3183 15 3 12.7057 5.7057
0.0417 66.0 2442 2.8289 0.4726 0.2532 0.4242 0.4243 0.8746 0.8667 7.9159 15 3 12.3363 3.003
0.0365 67.0 2479 2.8272 0.4752 0.2506 0.4222 0.4218 0.8732 0.8673 8.1652 15 3 12.5165 4.8048
0.0372 68.0 2516 2.8469 0.4726 0.2491 0.4225 0.423 0.873 0.8665 8.1802 17 4 12.5796 5.4054
0.0363 69.0 2553 2.8233 0.4745 0.2554 0.4244 0.4239 0.8751 0.8672 8.0601 16 4 12.2342 3.6036
0.0356 70.0 2590 2.8652 0.4737 0.2471 0.4169 0.4167 0.8735 0.8658 8.03 17 4 12.3273 5.1051
0.0366 71.0 2627 2.8722 0.4838 0.2598 0.4274 0.428 0.8767 0.869 8.0541 14 4 12.2913 3.003
0.0334 72.0 2664 2.8650 0.4708 0.2508 0.4194 0.4195 0.873 0.8674 8.2252 16 4 12.6426 4.2042
0.0328 73.0 2701 2.8827 0.479 0.2498 0.4221 0.422 0.8753 0.8683 8.1802 16 4 12.4835 3.3033
0.0322 74.0 2738 2.8599 0.479 0.2524 0.4295 0.43 0.8746 0.8689 8.2583 17 4 12.6727 4.2042
0.0308 75.0 2775 2.8559 0.4781 0.255 0.4279 0.4292 0.8766 0.8687 8.042 14 4 12.3033 2.4024
0.0304 76.0 2812 2.8364 0.4779 0.2581 0.4286 0.4287 0.8759 0.8682 7.994 17 3 12.3063 3.3033
0.0322 77.0 2849 2.8167 0.472 0.2489 0.4222 0.4225 0.8746 0.8673 8.003 17 4 12.3754 4.8048
0.0296 78.0 2886 2.8835 0.4716 0.2541 0.4217 0.4219 0.8734 0.8679 8.2252 17 4 12.6787 4.5045
0.0284 79.0 2923 2.8712 0.4729 0.2526 0.4228 0.4229 0.874 0.8672 8.1772 18 4 12.5495 3.6036
0.0286 80.0 2960 2.8709 0.4826 0.2596 0.4328 0.4324 0.877 0.8705 8.1592 18 4 12.4234 4.2042
0.0287 81.0 2997 2.8556 0.4746 0.2558 0.4228 0.4236 0.8747 0.8681 8.1381 17 4 12.3994 3.003
0.0287 82.0 3034 2.8867 0.4788 0.2617 0.429 0.4291 0.8757 0.8701 8.3273 17 4 12.6997 5.1051
0.0298 83.0 3071 2.8793 0.4828 0.2609 0.4306 0.4295 0.8757 0.8702 8.2673 17 4 12.6066 4.5045
0.0266 84.0 3108 2.8795 0.472 0.2499 0.4208 0.4207 0.8742 0.8677 8.1742 15 4 12.5345 3.6036
0.0257 85.0 3145 2.8788 0.48 0.2543 0.4244 0.4247 0.876 0.8686 8.1321 14 4 12.3874 2.7027
0.0255 86.0 3182 2.9130 0.4868 0.266 0.4307 0.4304 0.8762 0.8702 8.1652 15 4 12.5285 3.3033
0.0254 87.0 3219 2.9050 0.4847 0.2627 0.4327 0.432 0.877 0.8702 8.042 16 4 12.4324 3.3033
0.0233 88.0 3256 2.9014 0.4855 0.2615 0.433 0.4328 0.8758 0.8701 8.2613 16 4 12.5706 3.9039
0.0268 89.0 3293 2.8937 0.487 0.2586 0.4316 0.4317 0.8763 0.8707 8.2402 15 4 12.5616 4.2042
0.0243 90.0 3330 2.8926 0.4838 0.2584 0.4271 0.4268 0.8765 0.8695 8.1171 14 4 12.3483 3.3033
0.0248 91.0 3367 2.8870 0.4775 0.2503 0.4223 0.4222 0.8748 0.8678 8.1201 14 4 12.4354 3.3033
0.0237 92.0 3404 2.8978 0.4816 0.2556 0.4275 0.4275 0.8752 0.8688 8.0991 14 4 12.4685 2.7027
0.0244 93.0 3441 2.9025 0.4778 0.2506 0.4246 0.4249 0.8747 0.868 8.039 14 4 12.4174 3.003
0.0227 94.0 3478 2.9164 0.4733 0.2486 0.4199 0.4204 0.8745 0.8669 7.973 14 4 12.3123 2.7027
0.0215 95.0 3515 2.9183 0.4795 0.2495 0.4233 0.4231 0.8751 0.8682 8.03 14 4 12.4084 3.003
0.0225 96.0 3552 2.9207 0.4763 0.2463 0.4204 0.4206 0.8752 0.8677 8.0511 14 4 12.3934 2.7027
0.0208 97.0 3589 2.9226 0.4815 0.2556 0.4271 0.4276 0.8758 0.869 8.0871 14 4 12.4144 2.7027
0.0225 98.0 3626 2.9234 0.4832 0.2576 0.4285 0.4281 0.8762 0.8693 8.1351 16 4 12.4595 3.003
0.0219 99.0 3663 2.9243 0.4809 0.2543 0.4249 0.4249 0.8754 0.8686 8.1141 14 4 12.4775 2.7027
0.0214 100.0 3700 2.9239 0.4821 0.2554 0.4273 0.4271 0.8753 0.8686 8.1231 14 4 12.4805 2.7027

Framework versions

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