| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-newsroom | |
| model-index: | |
| - name: pegasus-newsroom-headline_writer_57k | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # pegasus-newsroom-headline_writer_57k | |
| 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: 1.3599 | |
| - Rouge1: 42.2586 | |
| - Rouge2: 23.2731 | |
| - Rougel: 35.8685 | |
| - Rougelsum: 36.0581 | |
| - Gen Len: 34.3651 | |
| ## 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: 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: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 1.5213 | 1.0 | 5670 | 1.4040 | 41.8648 | 22.8205 | 35.3983 | 35.535 | 34.8817 | | |
| | 1.4171 | 2.0 | 11340 | 1.3672 | 42.26 | 23.2611 | 35.8016 | 35.9753 | 34.3492 | | |
| | 1.3722 | 3.0 | 17010 | 1.3599 | 42.2586 | 23.2731 | 35.8685 | 36.0581 | 34.3651 | | |
| ### Framework versions | |
| - Transformers 4.23.1 | |
| - Pytorch 1.12.1+cu113 | |
| - Datasets 2.6.0 | |
| - Tokenizers 0.13.1 | |