--- tags: - generated_from_trainer datasets: - samsum metrics: - rouge model-index: - name: pegasus-large-finetuned-samsum-test results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: samsum type: samsum config: samsum split: test args: samsum metrics: - name: Rouge1 type: rouge value: 51.4013 --- # pegasus-large-finetuned-samsum-test This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the samsum dataset. It achieves the following results on the evaluation set: - Loss: 1.3835 - Rouge1: 51.4013 - Rouge2: 27.1012 - Rougel: 43.4218 - Rougelsum: 47.1203 - Gen Len: 20.6996 ## 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: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | 1.4761 | 1.0 | 7366 | 1.3835 | 51.4013 | 27.1012 | 43.4218 | 47.1203 | 20.6996 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3