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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: text_shortening_model_v13 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# text_shortening_model_v13 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9666 |
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- Rouge1: 0.579 |
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- Rouge2: 0.3396 |
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- Rougel: 0.5272 |
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- Rougelsum: 0.5263 |
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- Bert precision: 0.8964 |
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- Bert recall: 0.8985 |
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- Average word count: 10.9714 |
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- Max word count: 16 |
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- Min word count: 6 |
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- Average token count: 16.1071 |
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- % shortened texts with length > 12: 22.8571 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 60 |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:| |
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| 1.4719 | 1.0 | 62 | 1.5878 | 0.5604 | 0.3377 | 0.508 | 0.5076 | 0.8858 | 0.8969 | 12.3214 | 17 | 4 | 17.0429 | 55.7143 | |
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| 1.2908 | 2.0 | 124 | 1.5191 | 0.5675 | 0.3397 | 0.5143 | 0.5145 | 0.8902 | 0.8974 | 11.8071 | 17 | 4 | 16.65 | 47.8571 | |
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| 1.1543 | 3.0 | 186 | 1.4723 | 0.5723 | 0.3432 | 0.5282 | 0.5278 | 0.8938 | 0.8988 | 11.45 | 17 | 5 | 16.4 | 39.2857 | |
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| 1.0903 | 4.0 | 248 | 1.4651 | 0.5785 | 0.3397 | 0.5266 | 0.5264 | 0.8888 | 0.9011 | 12.1071 | 17 | 7 | 17.2571 | 50.0 | |
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| 1.0048 | 5.0 | 310 | 1.4482 | 0.5768 | 0.334 | 0.5245 | 0.5249 | 0.8903 | 0.9007 | 12.1 | 17 | 6 | 17.1357 | 50.0 | |
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| 0.971 | 6.0 | 372 | 1.4231 | 0.5822 | 0.343 | 0.5346 | 0.5347 | 0.8954 | 0.9007 | 11.4071 | 16 | 6 | 16.4357 | 37.8571 | |
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| 0.9113 | 7.0 | 434 | 1.4383 | 0.585 | 0.3532 | 0.5375 | 0.5374 | 0.8937 | 0.9029 | 11.8143 | 17 | 6 | 16.8714 | 42.1429 | |
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| 0.8767 | 8.0 | 496 | 1.4240 | 0.5913 | 0.3592 | 0.5455 | 0.5449 | 0.8951 | 0.904 | 11.7071 | 16 | 6 | 16.8286 | 39.2857 | |
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| 0.8384 | 9.0 | 558 | 1.4367 | 0.5855 | 0.3567 | 0.5418 | 0.5413 | 0.8965 | 0.9016 | 11.4214 | 16 | 6 | 16.3857 | 34.2857 | |
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| 0.7953 | 10.0 | 620 | 1.4470 | 0.5878 | 0.3566 | 0.535 | 0.5346 | 0.8958 | 0.901 | 11.5143 | 16 | 6 | 16.4786 | 37.8571 | |
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| 0.7705 | 11.0 | 682 | 1.4686 | 0.585 | 0.3538 | 0.5325 | 0.5322 | 0.894 | 0.9002 | 11.6 | 16 | 7 | 16.75 | 37.8571 | |
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| 0.7354 | 12.0 | 744 | 1.4709 | 0.5875 | 0.3533 | 0.5415 | 0.5411 | 0.8947 | 0.9034 | 11.55 | 16 | 6 | 16.6643 | 35.7143 | |
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| 0.6957 | 13.0 | 806 | 1.5007 | 0.5912 | 0.3556 | 0.549 | 0.5481 | 0.8963 | 0.9027 | 11.5 | 16 | 7 | 16.6429 | 33.5714 | |
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| 0.6853 | 14.0 | 868 | 1.5181 | 0.5778 | 0.3461 | 0.5356 | 0.5348 | 0.8936 | 0.8993 | 11.4286 | 16 | 6 | 16.4571 | 28.5714 | |
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| 0.6519 | 15.0 | 930 | 1.5308 | 0.5817 | 0.3467 | 0.5355 | 0.5345 | 0.894 | 0.901 | 11.4714 | 16 | 7 | 16.5571 | 30.7143 | |
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| 0.656 | 16.0 | 992 | 1.5374 | 0.5821 | 0.3458 | 0.5331 | 0.5321 | 0.8961 | 0.8994 | 11.1429 | 16 | 6 | 16.1429 | 26.4286 | |
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| 0.6235 | 17.0 | 1054 | 1.5780 | 0.5913 | 0.352 | 0.5454 | 0.5452 | 0.8964 | 0.9045 | 11.4857 | 16 | 6 | 16.6929 | 29.2857 | |
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| 0.608 | 18.0 | 1116 | 1.6061 | 0.5871 | 0.3545 | 0.5436 | 0.5432 | 0.8953 | 0.9027 | 11.3786 | 16 | 6 | 16.6714 | 30.0 | |
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| 0.5764 | 19.0 | 1178 | 1.6206 | 0.5923 | 0.3592 | 0.5463 | 0.5458 | 0.8972 | 0.9026 | 11.2929 | 16 | 6 | 16.3857 | 30.7143 | |
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| 0.5657 | 20.0 | 1240 | 1.6333 | 0.5801 | 0.3407 | 0.5327 | 0.5322 | 0.894 | 0.9002 | 11.35 | 16 | 6 | 16.45 | 30.0 | |
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| 0.5405 | 21.0 | 1302 | 1.6460 | 0.5833 | 0.3433 | 0.5374 | 0.5366 | 0.8952 | 0.8978 | 11.0 | 16 | 6 | 16.1357 | 25.0 | |
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| 0.5335 | 22.0 | 1364 | 1.6747 | 0.5782 | 0.346 | 0.5376 | 0.5369 | 0.8977 | 0.8972 | 10.6857 | 16 | 6 | 15.6 | 22.1429 | |
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| 0.5398 | 23.0 | 1426 | 1.6644 | 0.5849 | 0.3528 | 0.542 | 0.5422 | 0.9003 | 0.8991 | 10.8429 | 16 | 6 | 15.7071 | 21.4286 | |
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| 0.5186 | 24.0 | 1488 | 1.6894 | 0.5741 | 0.3463 | 0.5341 | 0.5336 | 0.8961 | 0.8971 | 10.8714 | 16 | 6 | 15.8571 | 21.4286 | |
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| 0.4855 | 25.0 | 1550 | 1.6943 | 0.5849 | 0.3462 | 0.5368 | 0.5365 | 0.8955 | 0.8988 | 11.1071 | 16 | 6 | 16.0929 | 28.5714 | |
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| 0.4889 | 26.0 | 1612 | 1.7254 | 0.575 | 0.3487 | 0.5346 | 0.5347 | 0.8987 | 0.8978 | 10.7214 | 16 | 6 | 15.7357 | 21.4286 | |
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| 0.4822 | 27.0 | 1674 | 1.7385 | 0.5782 | 0.3446 | 0.5338 | 0.5335 | 0.8989 | 0.8984 | 10.7143 | 16 | 5 | 15.6714 | 22.8571 | |
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| 0.4725 | 28.0 | 1736 | 1.7633 | 0.5795 | 0.3447 | 0.5368 | 0.5362 | 0.8983 | 0.8982 | 10.7 | 16 | 5 | 15.7429 | 22.1429 | |
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| 0.4507 | 29.0 | 1798 | 1.7773 | 0.5714 | 0.3382 | 0.5293 | 0.5297 | 0.8954 | 0.898 | 10.9286 | 16 | 6 | 16.0429 | 25.0 | |
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| 0.4637 | 30.0 | 1860 | 1.7915 | 0.5787 | 0.3438 | 0.536 | 0.5359 | 0.8958 | 0.8997 | 11.1714 | 16 | 6 | 16.2429 | 27.1429 | |
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| 0.4589 | 31.0 | 1922 | 1.8094 | 0.5755 | 0.3387 | 0.5278 | 0.5279 | 0.8934 | 0.8982 | 11.2143 | 16 | 6 | 16.4286 | 27.8571 | |
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| 0.4234 | 32.0 | 1984 | 1.8093 | 0.5783 | 0.3429 | 0.5315 | 0.5319 | 0.8957 | 0.8983 | 11.0643 | 16 | 6 | 16.1786 | 25.7143 | |
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| 0.4398 | 33.0 | 2046 | 1.8084 | 0.5842 | 0.3471 | 0.5355 | 0.5347 | 0.8964 | 0.9004 | 11.1786 | 16 | 6 | 16.3143 | 25.0 | |
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| 0.4168 | 34.0 | 2108 | 1.8310 | 0.5839 | 0.3467 | 0.5348 | 0.5351 | 0.8972 | 0.8994 | 11.0429 | 16 | 6 | 16.1786 | 24.2857 | |
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| 0.4174 | 35.0 | 2170 | 1.8377 | 0.5802 | 0.3436 | 0.5306 | 0.5302 | 0.8964 | 0.8992 | 11.1214 | 16 | 6 | 16.2571 | 26.4286 | |
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| 0.4149 | 36.0 | 2232 | 1.8449 | 0.5791 | 0.3461 | 0.5306 | 0.5297 | 0.8951 | 0.9002 | 11.2929 | 16 | 6 | 16.5 | 27.1429 | |
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| 0.4029 | 37.0 | 2294 | 1.8459 | 0.5812 | 0.3451 | 0.533 | 0.5322 | 0.898 | 0.8986 | 10.8857 | 16 | 6 | 15.9286 | 22.1429 | |
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| 0.386 | 38.0 | 2356 | 1.8505 | 0.5861 | 0.3513 | 0.5373 | 0.5364 | 0.8969 | 0.9014 | 11.2429 | 16 | 6 | 16.3357 | 27.1429 | |
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| 0.3946 | 39.0 | 2418 | 1.8668 | 0.5877 | 0.3551 | 0.539 | 0.5377 | 0.8977 | 0.9014 | 11.1857 | 16 | 6 | 16.3071 | 25.7143 | |
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| 0.3889 | 40.0 | 2480 | 1.8692 | 0.585 | 0.3463 | 0.5347 | 0.5335 | 0.8985 | 0.9007 | 11.0357 | 16 | 6 | 16.1214 | 22.8571 | |
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| 0.3769 | 41.0 | 2542 | 1.8718 | 0.5795 | 0.3461 | 0.5336 | 0.5323 | 0.897 | 0.899 | 10.9286 | 16 | 6 | 16.0214 | 21.4286 | |
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| 0.3667 | 42.0 | 2604 | 1.9021 | 0.5803 | 0.3494 | 0.5313 | 0.5306 | 0.8965 | 0.8996 | 11.1071 | 16 | 6 | 16.2714 | 23.5714 | |
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| 0.3603 | 43.0 | 2666 | 1.9108 | 0.584 | 0.3486 | 0.5363 | 0.5353 | 0.8964 | 0.8987 | 11.0571 | 16 | 6 | 16.2714 | 22.8571 | |
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| 0.3732 | 44.0 | 2728 | 1.8997 | 0.5807 | 0.3458 | 0.533 | 0.5319 | 0.8973 | 0.899 | 10.9286 | 16 | 6 | 16.15 | 21.4286 | |
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| 0.3731 | 45.0 | 2790 | 1.9185 | 0.5816 | 0.3465 | 0.5319 | 0.5316 | 0.8984 | 0.899 | 10.8571 | 16 | 6 | 15.9429 | 19.2857 | |
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| 0.3663 | 46.0 | 2852 | 1.9283 | 0.5799 | 0.3443 | 0.5323 | 0.5312 | 0.8962 | 0.9002 | 11.2 | 16 | 7 | 16.3071 | 26.4286 | |
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| 0.3643 | 47.0 | 2914 | 1.9332 | 0.5769 | 0.3474 | 0.5287 | 0.5278 | 0.8962 | 0.8998 | 11.0643 | 16 | 6 | 16.3429 | 22.8571 | |
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| 0.3638 | 48.0 | 2976 | 1.9375 | 0.5766 | 0.3465 | 0.5274 | 0.5271 | 0.8956 | 0.9001 | 11.2929 | 16 | 7 | 16.4786 | 27.8571 | |
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| 0.3555 | 49.0 | 3038 | 1.9419 | 0.5682 | 0.3353 | 0.5215 | 0.5212 | 0.8947 | 0.8968 | 10.9143 | 16 | 6 | 16.0571 | 21.4286 | |
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| 0.3678 | 50.0 | 3100 | 1.9431 | 0.5815 | 0.3461 | 0.5313 | 0.531 | 0.8977 | 0.9003 | 10.9714 | 16 | 6 | 16.0286 | 22.1429 | |
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| 0.3439 | 51.0 | 3162 | 1.9477 | 0.5771 | 0.3414 | 0.5277 | 0.5271 | 0.8962 | 0.8993 | 11.0857 | 16 | 6 | 16.1857 | 25.0 | |
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| 0.3538 | 52.0 | 3224 | 1.9492 | 0.5764 | 0.3386 | 0.5269 | 0.5262 | 0.8959 | 0.899 | 11.05 | 16 | 6 | 16.1286 | 23.5714 | |
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| 0.3556 | 53.0 | 3286 | 1.9604 | 0.5762 | 0.3343 | 0.5258 | 0.5254 | 0.8955 | 0.8989 | 11.1643 | 16 | 6 | 16.2429 | 27.8571 | |
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| 0.3385 | 54.0 | 3348 | 1.9604 | 0.5784 | 0.3389 | 0.5282 | 0.5271 | 0.8966 | 0.8982 | 10.95 | 16 | 6 | 16.05 | 23.5714 | |
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| 0.3353 | 55.0 | 3410 | 1.9585 | 0.5796 | 0.3449 | 0.5313 | 0.531 | 0.8969 | 0.8996 | 11.0786 | 16 | 6 | 16.1071 | 25.7143 | |
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| 0.3472 | 56.0 | 3472 | 1.9639 | 0.5778 | 0.3379 | 0.5287 | 0.5282 | 0.8964 | 0.899 | 11.0857 | 16 | 6 | 16.1214 | 25.7143 | |
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| 0.3352 | 57.0 | 3534 | 1.9661 | 0.5758 | 0.335 | 0.5254 | 0.5246 | 0.8958 | 0.8984 | 11.0571 | 16 | 6 | 16.1429 | 25.0 | |
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| 0.3401 | 58.0 | 3596 | 1.9666 | 0.5754 | 0.3353 | 0.5255 | 0.5249 | 0.8952 | 0.898 | 11.0643 | 16 | 6 | 16.2 | 24.2857 | |
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| 0.3446 | 59.0 | 3658 | 1.9664 | 0.5829 | 0.3413 | 0.5312 | 0.5309 | 0.8969 | 0.8994 | 10.9857 | 16 | 6 | 16.1357 | 23.5714 | |
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| 0.3376 | 60.0 | 3720 | 1.9666 | 0.579 | 0.3396 | 0.5272 | 0.5263 | 0.8964 | 0.8985 | 10.9714 | 16 | 6 | 16.1071 | 22.8571 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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