| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - arxiv_summarization_dataset | |
| metrics: | |
| - rouge | |
| base_model: sshleifer/distilbart-cnn-12-6 | |
| model-index: | |
| - name: distilbart-cnn-12-6-finetuned-30k-3epoch | |
| results: | |
| - task: | |
| type: text2text-generation | |
| name: Sequence-to-sequence Language Modeling | |
| dataset: | |
| name: arxiv_summarization_dataset | |
| type: arxiv_summarization_dataset | |
| config: section | |
| split: test[:2000] | |
| args: section | |
| metrics: | |
| - type: rouge | |
| value: 43.696 | |
| name: Rouge1 | |
| <!-- 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-finetuned-30k-3epoch | |
| This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the arxiv_summarization_dataset dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 2.3411 | |
| - Rouge1: 43.696 | |
| - Rouge2: 15.6681 | |
| - Rougel: 25.6889 | |
| - Rougelsum: 38.574 | |
| - Gen Len: 121.98 | |
| ## 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: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:| | |
| | 2.7304 | 1.0 | 3750 | 2.4322 | 43.0913 | 15.1302 | 25.2555 | 38.0346 | 122.3755 | | |
| | 2.3518 | 2.0 | 7500 | 2.3613 | 43.8799 | 15.6977 | 25.6984 | 38.7646 | 122.6945 | | |
| | 2.2318 | 3.0 | 11250 | 2.3411 | 43.696 | 15.6681 | 25.6889 | 38.574 | 121.98 | | |
| ### Framework versions | |
| - Transformers 4.30.2 | |
| - Pytorch 2.0.0 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.13.3 | |