--- tags: - generated_from_trainer metrics: - rouge model-index: - name: pegasus-newsroom-headline_writer results: [] --- # pegasus-newsroom-headline_writer This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.3988 - Rouge1: 41.8748 - Rouge2: 23.1947 - Rougel: 35.6263 - Rougelsum: 35.7355 - Gen Len: 34.1266 ## 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: 1 - eval_batch_size: 1 - 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 | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | 1.5784 | 1.0 | 31200 | 1.4287 | 41.4257 | 22.9355 | 35.3299 | 35.4648 | 34.4677 | | 1.3501 | 2.0 | 62400 | 1.3955 | 41.9119 | 23.1912 | 35.6698 | 35.7479 | 33.8672 | | 1.2417 | 3.0 | 93600 | 1.3988 | 41.8748 | 23.1947 | 35.6263 | 35.7355 | 34.1266 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.9.0+cu111 - Datasets 1.14.0 - Tokenizers 0.10.3