| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-multi_news | |
| model-index: | |
| - name: pegasus-multi_news-summarizer_01 | |
| 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-multi_news-summarizer_01 | |
| 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: 1.2794 | |
| - Rouge1: 52.1693 | |
| - Rouge2: 34.8989 | |
| - Rougel: 41.2385 | |
| - Rougelsum: 48.4365 | |
| - Gen Len: 98.6433 | |
| ## 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 | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:| | |
| | 1.3936 | 1.0 | 16113 | 1.2972 | 51.5747 | 34.2062 | 40.7279 | 47.7783 | 95.0004 | | |
| | 1.3664 | 2.0 | 32226 | 1.2817 | 52.1077 | 34.8189 | 41.1614 | 48.3894 | 100.3265 | | |
| | 1.3002 | 3.0 | 48339 | 1.2794 | 52.1693 | 34.8989 | 41.2385 | 48.4365 | 98.6433 | | |
| ### Framework versions | |
| - Transformers 4.12.3 | |
| - Pytorch 1.9.0+cu111 | |
| - Datasets 1.15.1 | |
| - Tokenizers 0.10.3 | |