| license: apache-2.0 | |
| tags: | |
| - summarization | |
| - generated_from_trainer | |
| datasets: | |
| - multi_news | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: multi-news-diff-weight | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: multi_news | |
| type: multi_news | |
| config: default | |
| split: train[:95%] | |
| args: default | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 9.815 | |
| <!-- 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. --> | |
| # multi-news-diff-weight | |
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 2.3427 | |
| - Rouge1: 9.815 | |
| - Rouge2: 3.8774 | |
| - Rougel: 7.6169 | |
| - Rougelsum: 8.9863 | |
| ## 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: 5e-05 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 2 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:| | |
| | 2.75 | 1.0 | 19225 | 2.4494 | 9.5021 | 3.5429 | 7.3531 | 8.6912 | | |
| | 2.456 | 2.0 | 38450 | 2.3665 | 9.8103 | 3.8494 | 7.6256 | 8.9991 | | |
| | 2.285 | 3.0 | 57675 | 2.3427 | 9.815 | 3.8774 | 7.6169 | 8.9863 | | |
| ### Framework versions | |
| - Transformers 4.29.1 | |
| - Pytorch 2.0.0 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |