| license: mit | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - multi_news | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: bart_large_summarise_v3 | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: multi_news | |
| type: multi_news | |
| config: default | |
| split: train | |
| args: default | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 0.3914 | |
| <!-- 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. --> | |
| # bart_large_summarise_v3 | |
| This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the multi_news dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 4.1359 | |
| - Rouge1: 0.3914 | |
| - Rouge2: 0.1399 | |
| - Rougel: 0.2039 | |
| - Rougelsum: 0.3504 | |
| - Gen Len: 141.64 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 10 | |
| - label_smoothing_factor: 0.1 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.23.1 | |
| - Pytorch 1.12.1+cu113 | |
| - Datasets 2.6.1 | |
| - Tokenizers 0.13.1 | |