--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer metrics: - rouge model-index: - name: text_shortening_model_v8 results: [] --- # text_shortening_model_v8 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: 2.3248 - Rouge1: 0.43 - Rouge2: 0.2172 - Rougel: 0.3684 - Rougelsum: 0.3674 - Bert precision: 0.8551 - Bert recall: 0.8369 - Average word count: 9.8214 - Max word count: 17 - Min word count: 5 - Average token count: 15.5857 - % shortened texts with length > 12: 17.1429 ## 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 | % shortened texts with length > 12 | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:| | 0.2688 | 1.0 | 8 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.284 | 2.0 | 16 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.264 | 3.0 | 24 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2564 | 4.0 | 32 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2727 | 5.0 | 40 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2924 | 6.0 | 48 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2666 | 7.0 | 56 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2662 | 8.0 | 64 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2631 | 9.0 | 72 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2844 | 10.0 | 80 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2653 | 11.0 | 88 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2649 | 12.0 | 96 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2972 | 13.0 | 104 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2553 | 14.0 | 112 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.261 | 15.0 | 120 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2832 | 16.0 | 128 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2635 | 17.0 | 136 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2484 | 18.0 | 144 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2612 | 19.0 | 152 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2996 | 20.0 | 160 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2562 | 21.0 | 168 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2503 | 22.0 | 176 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2763 | 23.0 | 184 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2692 | 24.0 | 192 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.284 | 25.0 | 200 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2838 | 26.0 | 208 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2729 | 27.0 | 216 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2685 | 28.0 | 224 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2599 | 29.0 | 232 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2829 | 30.0 | 240 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2275 | 31.0 | 248 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2605 | 32.0 | 256 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2855 | 33.0 | 264 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.251 | 34.0 | 272 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2629 | 35.0 | 280 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2679 | 36.0 | 288 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2453 | 37.0 | 296 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2853 | 38.0 | 304 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2542 | 39.0 | 312 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2627 | 40.0 | 320 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2668 | 41.0 | 328 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2742 | 42.0 | 336 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2746 | 43.0 | 344 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2768 | 44.0 | 352 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2729 | 45.0 | 360 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2729 | 46.0 | 368 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2788 | 47.0 | 376 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.286 | 48.0 | 384 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2484 | 49.0 | 392 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | | 0.2679 | 50.0 | 400 | 2.3248 | 0.43 | 0.2172 | 0.3684 | 0.3674 | 0.8551 | 0.8369 | 9.8214 | 17 | 5 | 15.5857 | 17.1429 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3