| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-multi_news | |
| model-index: | |
| - name: pegasus-multi_news-headline | |
| 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-headline | |
| 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: 1.4421 | |
| - Rouge1: 41.616 | |
| - Rouge2: 22.922 | |
| - Rougel: 35.2189 | |
| - Rougelsum: 35.3561 | |
| - Gen Len: 33.9532 | |
| ## 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 | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 1.6637 | 1.0 | 31200 | 1.4877 | 41.0996 | 22.579 | 34.9311 | 35.0611 | 34.3431 | | |
| | 1.4395 | 2.0 | 62400 | 1.4388 | 41.6075 | 22.8274 | 35.2051 | 35.3526 | 33.7965 | | |
| | 1.3137 | 3.0 | 93600 | 1.4421 | 41.616 | 22.922 | 35.2189 | 35.3561 | 33.9532 | | |
| ### Framework versions | |
| - Transformers 4.12.2 | |
| - Pytorch 1.9.0+cu111 | |
| - Datasets 1.14.0 | |
| - Tokenizers 0.10.3 | |