--- license: apache-2.0 tags: - summarization - generated_from_trainer datasets: - samsum metrics: - rouge model-index: - name: t5-v1_1-small-finetuned-samsum results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: samsum type: samsum config: samsum split: train args: samsum metrics: - name: Rouge1 type: rouge value: 0.40608242084369006 --- # t5-v1_1-small-finetuned-samsum This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the samsum dataset. It achieves the following results on the evaluation set: - Loss: 2.0053 - Rouge1: 0.4061 - Rouge2: 0.1804 - Rougel: 0.3478 - Rougelsum: 0.3774 ## 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: 5.6e-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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| | 3.9788 | 1.0 | 1842 | 2.2499 | 0.3743 | 0.1569 | 0.3191 | 0.3486 | | 2.9091 | 2.0 | 3684 | 2.1052 | 0.3875 | 0.1680 | 0.3329 | 0.3607 | | 2.6807 | 3.0 | 5526 | 2.0270 | 0.4009 | 0.1778 | 0.3439 | 0.3734 | | 2.5917 | 4.0 | 7368 | 2.0053 | 0.4061 | 0.1804 | 0.3478 | 0.3774 | ### Framework versions - Transformers 4.24.0 - Pytorch 1.12.1+cu113 - Datasets 2.7.1 - Tokenizers 0.13.2