| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| base_model: google/pegasus-multi_news | |
| model-index: | |
| - name: pegasus-multi_news-commentaries_hdwriter | |
| 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-commentaries_hdwriter | |
| 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: 2.7259 | |
| - Rouge1: 21.3899 | |
| - Rouge2: 6.2409 | |
| - Rougel: 16.6172 | |
| - Rougelsum: 17.808 | |
| - Gen Len: 34.7016 | |
| ## 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: 5 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | |
| | 2.847 | 1.0 | 4710 | 2.7513 | 20.5559 | 5.9762 | 16.1223 | 17.2872 | 35.81 | | |
| | 2.6399 | 2.0 | 9420 | 2.6890 | 21.2052 | 6.0104 | 16.5753 | 17.6517 | 34.5242 | | |
| | 2.3811 | 3.0 | 14130 | 2.6904 | 21.2358 | 6.1416 | 16.6053 | 17.7067 | 34.6157 | | |
| | 2.2388 | 4.0 | 18840 | 2.7112 | 21.3806 | 6.1895 | 16.6909 | 17.7504 | 34.5227 | | |
| | 2.1589 | 5.0 | 23550 | 2.7259 | 21.3899 | 6.2409 | 16.6172 | 17.808 | 34.7016 | | |
| ### Framework versions | |
| - Transformers 4.15.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 1.17.0 | |
| - Tokenizers 0.10.3 | |