--- license: apache-2.0 tags: - generated_from_trainer datasets: - xsum metrics: - rouge model-index: - name: t5_finetuned_xsum_hr results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: xsum type: xsum config: default split: train args: default metrics: - name: Rouge1 type: rouge value: 29.1239 --- # t5_finetuned_xsum_hr This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset. It achieves the following results on the evaluation set: - Loss: 2.4224 - Rouge1: 29.1239 - Rouge2: 8.3165 - Rougel: 22.9946 - Rougelsum: 22.9996 - Gen Len: 18.819 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | 2.6839 | 1.0 | 12753 | 2.4474 | 28.721 | 8.0397 | 22.6568 | 22.6527 | 18.8324 | | 2.6425 | 2.0 | 25506 | 2.4224 | 29.1239 | 8.3165 | 22.9946 | 22.9996 | 18.819 | ### Framework versions - Transformers 4.21.0 - Pytorch 1.12.0 - Datasets 2.4.0 - Tokenizers 0.12.1