| license: apache-2.0 | |
| tags: | |
| - summarization | |
| datasets: | |
| - multi_news | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: distilbart-cnn-12-6-ftn-multi_news | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: summarization | |
| dataset: | |
| name: multi_news | |
| type: multi_news | |
| args: default | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 41.6136 | |
| - task: | |
| type: summarization | |
| name: Summarization | |
| dataset: | |
| name: multi_news | |
| type: multi_news | |
| config: default | |
| split: test | |
| metrics: | |
| - name: ROUGE-1 | |
| type: rouge | |
| value: 39.6512 | |
| verified: true | |
| - name: ROUGE-2 | |
| type: rouge | |
| value: 14.333 | |
| verified: true | |
| - name: ROUGE-L | |
| type: rouge | |
| value: 21.5797 | |
| verified: true | |
| - name: ROUGE-LSUM | |
| type: rouge | |
| value: 35.5793 | |
| verified: true | |
| - name: loss | |
| type: loss | |
| value: 5.507579803466797 | |
| verified: true | |
| - name: gen_len | |
| type: gen_len | |
| value: 132.1745 | |
| verified: true | |
| <!-- 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. --> | |
| # distilbart-cnn-12-6-ftn-multi_news | |
| This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the multi_news dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 3.8143 | |
| - Rouge1: 41.6136 | |
| - Rouge2: 14.7454 | |
| - Rougel: 23.3597 | |
| - Rougelsum: 36.1973 | |
| - Gen Len: 130.874 | |
| ## 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 | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 1 | |
| - mixed_precision_training: Native AMP | |
| - label_smoothing_factor: 0.1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 3.8821 | 0.89 | 2000 | 3.8143 | 41.6136 | 14.7454 | 23.3597 | 36.1973 | 130.874 | | |
| ### Framework versions | |
| - Transformers 4.20.1 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.3.2 | |
| - Tokenizers 0.12.1 | |