readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-cnn-pubmed-arxiv-v3-e4
    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. -->
  
  # bart-cnn-pubmed-arxiv-v3-e4
  
  This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7934
  - Rouge1: 54.2624
  - Rouge2: 35.6024
  - Rougel: 37.1697
  - Rougelsum: 51.5144
  - Gen Len: 141.9815
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 398  | 0.9533          | 52.3191 | 32.4576 | 33.2016 | 49.6502   | 142.0    |
  | 1.1154        | 2.0   | 796  | 0.8407          | 53.6639 | 34.3433 | 36.1893 | 50.9077   | 142.0    |
  | 0.6856        | 3.0   | 1194 | 0.7978          | 54.4723 | 36.1315 | 37.7891 | 51.902    | 142.0    |
  | 0.4943        | 4.0   | 1592 | 0.7934          | 54.2624 | 35.6024 | 37.1697 | 51.5144   | 141.9815 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  