| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-newsroom | |
| model-index: | |
| - name: pegasus-newsroom-rewriter | |
| 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-rewriter | |
| 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: 1.3424 | |
| - Rouge1: 46.6856 | |
| - Rouge2: 31.6377 | |
| - Rougel: 33.2741 | |
| - Rougelsum: 44.5003 | |
| - Gen Len: 126.58 | |
| ## 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: 4 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | No log | 1.0 | 450 | 1.4020 | 47.0593 | 32.2065 | 33.9168 | 44.901 | 126.32 | | |
| | 1.9944 | 2.0 | 900 | 1.3567 | 46.2635 | 30.9959 | 32.933 | 44.1659 | 126.48 | | |
| | 1.6511 | 3.0 | 1350 | 1.3449 | 46.1544 | 30.7257 | 32.693 | 43.9977 | 126.4 | | |
| | 1.5951 | 4.0 | 1800 | 1.3424 | 46.6856 | 31.6377 | 33.2741 | 44.5003 | 126.58 | | |
| ### Framework versions | |
| - Transformers 4.17.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 2.0.0 | |
| - Tokenizers 0.11.6 | |