--- tags: - generated_from_trainer metrics: - rouge model-index: - name: pegasus-multi_news_wires_hdwriter42k results: [] --- # pegasus-multi_news_wires_hdwriter42k This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.6427 - Rouge1: 37.3045 - Rouge2: 17.2478 - Rougel: 30.7768 - Rougelsum: 31.3514 - Gen Len: 34.6955 ## 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: 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: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | 1.7914 | 1.0 | 16875 | 1.6849 | 36.6608 | 17.005 | 30.4166 | 30.9289 | 35.4077 | | 1.6658 | 2.0 | 33750 | 1.6452 | 37.2837 | 17.3162 | 30.8358 | 31.3382 | 34.7757 | | 1.5478 | 3.0 | 50625 | 1.6427 | 37.3045 | 17.2478 | 30.7768 | 31.3514 | 34.6955 | ### Framework versions - Transformers 4.23.1 - Pytorch 1.12.1+cu113 - Datasets 2.6.1 - Tokenizers 0.13.1