| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-newsroom | |
| model-index: | |
| - name: pegasus-newsroom-headline_writer | |
| 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 | |
| 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: 1.3988 | |
| - Rouge1: 41.8748 | |
| - Rouge2: 23.1947 | |
| - Rougel: 35.6263 | |
| - Rougelsum: 35.7355 | |
| - Gen Len: 34.1266 | |
| ## 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 | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 1.5784 | 1.0 | 31200 | 1.4287 | 41.4257 | 22.9355 | 35.3299 | 35.4648 | 34.4677 | | |
| | 1.3501 | 2.0 | 62400 | 1.3955 | 41.9119 | 23.1912 | 35.6698 | 35.7479 | 33.8672 | | |
| | 1.2417 | 3.0 | 93600 | 1.3988 | 41.8748 | 23.1947 | 35.6263 | 35.7355 | 34.1266 | | |
| ### Framework versions | |
| - Transformers 4.11.3 | |
| - Pytorch 1.9.0+cu111 | |
| - Datasets 1.14.0 | |
| - Tokenizers 0.10.3 | |