--- license: apache-2.0 base_model: google-t5/t5-base tags: - generated_from_trainer model-index: - name: t5-abs-2209-2245-lr-0.001-bs-5-maxep-20 results: [] --- # t5-abs-2209-2245-lr-0.001-bs-5-maxep-20 This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.3529 - Rouge/rouge1: 0.4351 - Rouge/rouge2: 0.1856 - Rouge/rougel: 0.3628 - Rouge/rougelsum: 0.3635 - Bertscore/bertscore-precision: 0.8903 - Bertscore/bertscore-recall: 0.8895 - Bertscore/bertscore-f1: 0.8895 - Meteor: 0.3786 - Gen Len: 39.1091 ## 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: 0.001 - train_batch_size: 5 - eval_batch_size: 5 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 10 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge/rouge1 | Rouge/rouge2 | Rouge/rougel | Rouge/rougelsum | Bertscore/bertscore-precision | Bertscore/bertscore-recall | Bertscore/bertscore-f1 | Meteor | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:| | 1.8988 | 1.0 | 87 | 1.7718 | 0.4358 | 0.2026 | 0.3713 | 0.3725 | 0.8968 | 0.8886 | 0.8925 | 0.3812 | 36.0364 | | 1.6396 | 2.0 | 174 | 1.8159 | 0.4602 | 0.2124 | 0.3899 | 0.3907 | 0.8947 | 0.8923 | 0.8933 | 0.4147 | 38.8455 | | 1.4382 | 3.0 | 261 | 1.8736 | 0.4566 | 0.207 | 0.3863 | 0.387 | 0.8972 | 0.892 | 0.8944 | 0.4039 | 37.6091 | | 1.1395 | 4.0 | 348 | 1.8182 | 0.4505 | 0.197 | 0.3856 | 0.3852 | 0.8976 | 0.89 | 0.8937 | 0.3893 | 35.1455 | | 1.4623 | 5.0 | 435 | 2.2330 | 0.4078 | 0.1637 | 0.3412 | 0.342 | 0.8953 | 0.8848 | 0.8898 | 0.3459 | 33.8182 | | 1.5783 | 6.0 | 522 | 2.1105 | 0.4348 | 0.1859 | 0.365 | 0.3656 | 0.8955 | 0.889 | 0.892 | 0.3802 | 36.4 | | 1.4249 | 7.0 | 609 | 2.1361 | 0.4364 | 0.1875 | 0.3675 | 0.3685 | 0.8962 | 0.8894 | 0.8926 | 0.3808 | 36.0909 | | 1.3649 | 8.0 | 696 | 2.1641 | 0.4348 | 0.1822 | 0.3672 | 0.3677 | 0.8939 | 0.8886 | 0.891 | 0.3777 | 36.8364 | | 1.3433 | 9.0 | 783 | 2.2002 | 0.4382 | 0.183 | 0.3703 | 0.3707 | 0.8932 | 0.8888 | 0.8907 | 0.3833 | 37.2 | | 1.3906 | 10.0 | 870 | 2.2522 | 0.4359 | 0.1854 | 0.3644 | 0.3648 | 0.895 | 0.8897 | 0.8922 | 0.3804 | 37.1091 | | 1.4484 | 11.0 | 957 | 2.3514 | 0.4343 | 0.1854 | 0.3628 | 0.3632 | 0.89 | 0.8892 | 0.8892 | 0.3767 | 38.7273 | | 1.4984 | 12.0 | 1044 | 2.3529 | 0.4351 | 0.1853 | 0.3626 | 0.3632 | 0.8903 | 0.8895 | 0.8895 | 0.3783 | 39.1091 | | 1.5084 | 13.0 | 1131 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.4992 | 14.0 | 1218 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.5098 | 15.0 | 1305 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.5147 | 16.0 | 1392 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.494 | 17.0 | 1479 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.5169 | 18.0 | 1566 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.5183 | 19.0 | 1653 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | | 1.5101 | 20.0 | 1740 | 2.3529 | 0.4351 | 0.1856 | 0.3628 | 0.3635 | 0.8903 | 0.8895 | 0.8895 | 0.3786 | 39.1091 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1