--- license: mit tags: - generated_from_trainer model-index: - name: pegasus-samsum results: [] datasets: - samsum metrics: - rouge library_name: transformers --- # pegasus-samsum This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4963 ## Model description Original bart (Bidirectional Auto Regressive Transformers) paper : https://arxiv.org/abs/1910.13461 ## Training and evaluation data Fine-Tuned over 1 epoch. The improvements over facebook/bart-large-cnn over the rouge benchmark is as follows :
Rouge1 : 30.6 %
Rouge2 : 103 %
RougeL : 33.18 %
RougeLSum : 33.18 %
## Training procedure Please refer to https://github.com/dhivyeshrk/FineTuning-Facebook-bart-large-cnn ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.3689 | 0.54 | 500 | 1.4963 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3