--- license: apache-2.0 tags: - generated_from_trainer datasets: - billsum metrics: - rouge model-index: - name: t5_billsum results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: billsum type: billsum config: default split: ca_test args: default metrics: - name: Rouge1 type: rouge value: 0.1399 --- # t5_billsum This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset. It achieves the following results on the evaluation set: - Loss: 2.4902 - Rouge1: 0.1399 - Rouge2: 0.0492 - Rougel: 0.1163 - Rougelsum: 0.1161 - Gen Len: 19.0 ## 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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 62 | 2.7895 | 0.13 | 0.0368 | 0.1083 | 0.1082 | 19.0 | | No log | 2.0 | 124 | 2.5723 | 0.134 | 0.0448 | 0.1117 | 0.1114 | 19.0 | | No log | 3.0 | 186 | 2.5074 | 0.1418 | 0.0505 | 0.1171 | 0.1171 | 19.0 | | No log | 4.0 | 248 | 2.4902 | 0.1399 | 0.0492 | 0.1163 | 0.1161 | 19.0 | ### Framework versions - Transformers 4.30.1 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.13.3