| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-newsroom | |
| model-index: | |
| - name: pegasus-newsroom-headline_writer_oct22 | |
| 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_oct22 | |
| 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: 1.3462 | |
| - Rouge1: 41.8799 | |
| - Rouge2: 23.1785 | |
| - Rougel: 35.5346 | |
| - Rougelsum: 35.6203 | |
| - Gen Len: 34.3108 | |
| ## 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 | | |
| |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 1.4364 | 1.0 | 38400 | 1.3730 | 41.9525 | 23.0823 | 35.5435 | 35.6485 | 34.1161 | | |
| | 1.2483 | 2.0 | 76800 | 1.3430 | 42.1538 | 23.3302 | 35.8119 | 35.9063 | 33.9333 | | |
| | 1.1873 | 3.0 | 115200 | 1.3462 | 41.8799 | 23.1785 | 35.5346 | 35.6203 | 34.3108 | | |
| ### Framework versions | |
| - Transformers 4.22.2 | |
| - Pytorch 1.12.1+cu113 | |
| - Datasets 2.5.2 | |
| - Tokenizers 0.12.1 | |