--- license: apache-2.0 tags: - generated_from_trainer datasets: - wikihow metrics: - rouge model-index: - name: t5-small-finetuned-wikihow_3epoch_v2 results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: wikihow type: wikihow args: all metrics: - name: Rouge1 type: rouge value: 27.48 --- # t5-small-finetuned-wikihow_3epoch_v2 This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikihow dataset. It achieves the following results on the evaluation set: - Loss: 2.2758 - Rouge1: 27.48 - Rouge2: 10.7621 - Rougel: 23.4136 - Rougelsum: 26.7923 - Gen Len: 18.5424 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | 2.8423 | 0.13 | 5000 | 2.5715 | 25.2685 | 8.6964 | 21.229 | 24.5773 | 18.4479 | | 2.7345 | 0.25 | 10000 | 2.5236 | 24.982 | 8.7823 | 21.1609 | 24.3066 | 18.3631 | | 2.6811 | 0.38 | 15000 | 2.4911 | 25.7585 | 9.3372 | 21.8388 | 25.1052 | 18.3997 | | 2.6611 | 0.51 | 20000 | 2.4510 | 26.022 | 9.4708 | 22.0899 | 25.3236 | 18.5472 | | 2.6133 | 0.64 | 25000 | 2.4272 | 26.3481 | 9.6769 | 22.4484 | 25.7046 | 18.3863 | | 2.6083 | 0.76 | 30000 | 2.4108 | 26.4131 | 9.6643 | 22.4021 | 25.6958 | 18.5585 | | 2.5842 | 0.89 | 35000 | 2.3866 | 26.2852 | 9.7505 | 22.4525 | 25.5908 | 18.5485 | | 2.5554 | 1.02 | 40000 | 2.3816 | 26.3018 | 9.7218 | 22.3673 | 25.6515 | 18.4912 | | 2.4895 | 1.14 | 45000 | 2.3730 | 26.6439 | 9.9665 | 22.6593 | 25.9521 | 18.5635 | | 2.4781 | 1.27 | 50000 | 2.3541 | 26.8488 | 10.0364 | 22.8202 | 26.1598 | 18.4254 | | 2.4821 | 1.4 | 55000 | 2.3440 | 26.9511 | 10.2079 | 23.0133 | 26.2821 | 18.5712 | | 2.4593 | 1.53 | 60000 | 2.3370 | 26.945 | 10.3123 | 22.9245 | 26.2493 | 18.5978 | | 2.4521 | 1.65 | 65000 | 2.3309 | 26.9652 | 10.314 | 22.9657 | 26.298 | 18.4837 | | 2.4523 | 1.78 | 70000 | 2.3249 | 27.0548 | 10.4204 | 23.1286 | 26.379 | 18.4717 | | 2.4563 | 1.91 | 75000 | 2.3079 | 27.4563 | 10.6452 | 23.3985 | 26.7812 | 18.5642 | | 2.4229 | 2.03 | 80000 | 2.3115 | 27.0538 | 10.44 | 22.9957 | 26.349 | 18.5914 | | 2.3694 | 2.16 | 85000 | 2.3017 | 27.332 | 10.6556 | 23.3135 | 26.629 | 18.459 | | 2.3749 | 2.29 | 90000 | 2.2941 | 27.3294 | 10.5967 | 23.2039 | 26.6411 | 18.5179 | | 2.3779 | 2.42 | 95000 | 2.2891 | 27.3725 | 10.6539 | 23.3455 | 26.707 | 18.5367 | | 2.3638 | 2.54 | 100000 | 2.2895 | 27.3487 | 10.6738 | 23.2894 | 26.681 | 18.6128 | | 2.3549 | 2.67 | 105000 | 2.2833 | 27.408 | 10.6903 | 23.3575 | 26.7137 | 18.6035 | | 2.3652 | 2.8 | 110000 | 2.2788 | 27.561 | 10.8202 | 23.4672 | 26.8584 | 18.5565 | | 2.3553 | 2.93 | 115000 | 2.2758 | 27.48 | 10.7621 | 23.4136 | 26.7923 | 18.5424 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.10.0+cu111 - Datasets 2.0.0 - Tokenizers 0.11.6