| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-newsroom | |
| model-index: | |
| - name: pegasus-newsroom-malay_headlines | |
| 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-malay_headlines | |
| 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: 1.6603 | |
| - Rouge1: 42.6667 | |
| - Rouge2: 22.8739 | |
| - Rougel: 38.6684 | |
| - Rougelsum: 38.6928 | |
| - Gen Len: 34.7995 | |
| ## 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: 4 | |
| - eval_batch_size: 4 | |
| - 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 | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 1.9713 | 1.0 | 15310 | 1.8121 | 41.1469 | 21.5262 | 37.3081 | 37.3377 | 35.0939 | | |
| | 1.7917 | 2.0 | 30620 | 1.6913 | 42.4027 | 22.6089 | 38.4471 | 38.4699 | 34.8149 | | |
| | 1.7271 | 3.0 | 45930 | 1.6603 | 42.6667 | 22.8739 | 38.6684 | 38.6928 | 34.7995 | | |
| ### Framework versions | |
| - Transformers 4.12.2 | |
| - Pytorch 1.9.0+cu111 | |
| - Datasets 1.14.0 | |
| - Tokenizers 0.10.3 | |