readme: ---
  language: en
  tags:
  - generated_from_trainer
  datasets:
  - allenai/mslr2022
  model-index:
  - name: baseline
    results: []
  ---
  
  # Overview
  
  This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the [Cochrane](https://github.com/allenai/mslr-shared-task#cochrane-dataset) dataset. The model received as input 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 [Cochrane leaderboard](https://leaderboard.allenai.org/mslr-cochrane/submissions/public) for results on the blind test set. 
  
  It achieves the following results on the `validation` set:
  
  - Loss: 4.0216
  - Rouge1 Fmeasure Mean: 26.3026
  - Rouge2 Fmeasure Mean: 6.0324
  - Rougel Fmeasure Mean: 18.1513
  - Rougelsum Fmeasure Mean: 22.5031
  - Bertscore Hashcode: microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.11(hug_trans=4.22.0.dev0)-rescaled_fast-tokenizer
  - Bertscore F1 Mean: 20.5937
  - 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: 20
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Framework versions
  
  - Transformers 4.22.0.dev0
  - Pytorch 1.12.0
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  