--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer datasets: - xsum metrics: - rouge model-index: - name: test-summarization results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: xsum type: xsum config: default split: validation args: default metrics: - name: Rouge1 type: rouge value: 28.7363 --- # test-summarization 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: 2.4496 - Rouge1: 28.7363 - Rouge2: 8.023 - Rougel: 22.6496 - Rougelsum: 22.644 - Gen Len: 18.8226 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | 2.6873 | 1.0 | 25506 | 2.4496 | 28.7363 | 8.023 | 22.6496 | 22.644 | 18.8226 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1