| --- |
| language: en |
| tags: |
| - generated_from_trainer |
| datasets: |
| - allenai/mslr2022 |
| base_model: allenai/led-base-16384 |
| model-index: |
| - name: baseline |
| 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. --> |
|
|
| # Overview |
|
|
| This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the [MS^2](https://github.com/allenai/mslr-shared-task#ms2-dataset) dataset. The model received as input the background section and the titles and abstracts of up to 25 included studies for each example, concatenated by the `"</s>"` token. Global attention is applied to the special start token `"<s>"` and each of the document separator tokens `"</s>"`. The model slightly outperforms the reported results in the original paper: [MS2: Multi-Document Summarization of Medical Studies](https://arxiv.org/abs/2104.06486). See the [MS2 leaderboard](https://leaderboard.allenai.org/mslr-ms2/submissions/public) for results on the blind test set. |
|
|
| It achieves the following results on the evaluation set: |
| - Loss: 3.7602 |
| - Rouge1 Fmeasure Mean: 28.5338 |
| - Rouge2 Fmeasure Mean: 9.5060 |
| - RougeL Fmeasure Mean: 20.9321 |
| - RougeLsum Fmeasure Mean: 24.0998 |
| - Bertscore Hashcode: microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.11(hug_trans=4.21.0.dev0)-rescaled_fast-tokenizer |
| - Bertscore F1 Mean: 22.7619 |
| - Seed: 42 |
| - Model Name Or Path: allenai/led-base-16384 |
| - Doc Sep Token: `"</s>"` |
| |
| ## 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: 3e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| - label_smoothing_factor: 0.1 |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0.dev0 |
| - Pytorch 1.10.0 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
