| --- |
| library_name: transformers |
| base_model: google/pegasus-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: pegasus-large_1742608050.119433 |
| 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-large_1742608050.119433 |
| |
| This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.8799 |
| - Rouge1: 46.7629 |
| - Rouge2: 17.2538 |
| - Rougel: 27.775 |
| - Rougelsum: 32.6028 |
| - Gen Len: 85.8611 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | No log | 1.0 | 331 | 5.1130 | 48.5686 | 16.6489 | 28.3029 | 32.3136 | 71.2562 | |
| | 5.3363 | 2.0 | 662 | 5.0415 | 49.2151 | 17.0482 | 28.5422 | 32.4827 | 70.0833 | |
| | 5.3363 | 3.0 | 993 | 4.9860 | 48.9739 | 17.1901 | 28.4601 | 32.6516 | 72.8179 | |
| | 5.0157 | 4.0 | 1324 | 4.9619 | 48.2866 | 17.4271 | 28.1784 | 32.8011 | 77.8704 | |
| | 4.9426 | 5.0 | 1655 | 4.9329 | 48.7697 | 17.7741 | 28.6454 | 33.1256 | 76.4846 | |
| | 4.9426 | 6.0 | 1986 | 4.9133 | 48.0678 | 17.7361 | 28.3205 | 32.9328 | 79.4753 | |
| | 4.863 | 7.0 | 2317 | 4.8973 | 47.1789 | 17.4753 | 27.9637 | 32.7952 | 85.8056 | |
| | 4.8272 | 8.0 | 2648 | 4.8786 | 47.3498 | 17.2852 | 27.9143 | 32.7426 | 82.9198 | |
| | 4.8272 | 9.0 | 2979 | 4.8805 | 47.1749 | 17.4155 | 27.8944 | 32.7537 | 85.1111 | |
| | 4.7888 | 10.0 | 3310 | 4.8799 | 46.7629 | 17.2538 | 27.775 | 32.6028 | 85.8611 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.45.1 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
| |
