readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-cnn-pubmed-arxiv-pubmed-v3-e16
    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-pubmed-v3-e16
  
  This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8702
  - Rouge1: 56.1421
  - Rouge2: 41.3514
  - Rougel: 44.5146
  - Rougelsum: 54.3477
  - Gen Len: 142.0
  
  ## 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 398  | 0.9532          | 53.1932 | 32.9882 | 35.3852 | 50.6138   | 142.0    |
  | 1.1219        | 2.0   | 796  | 0.8252          | 54.1306 | 35.3774 | 37.4334 | 51.6652   | 142.0    |
  | 0.6698        | 3.0   | 1194 | 0.7828          | 53.8766 | 35.2945 | 39.2662 | 51.3239   | 142.0    |
  | 0.4435        | 4.0   | 1592 | 0.7744          | 53.9029 | 35.2716 | 37.5502 | 51.1179   | 142.0    |
  | 0.4435        | 5.0   | 1990 | 0.7644          | 53.8132 | 36.3643 | 39.9548 | 51.5348   | 141.4815 |
  | 0.3001        | 6.0   | 2388 | 0.7996          | 53.7376 | 36.2289 | 39.063  | 51.7514   | 142.0    |
  | 0.2045        | 7.0   | 2786 | 0.8009          | 54.4924 | 37.3594 | 40.033  | 52.1405   | 142.0    |
  | 0.1416        | 8.0   | 3184 | 0.7578          | 55.2039 | 39.0907 | 42.171  | 53.2835   | 142.0    |
  | 0.1058        | 9.0   | 3582 | 0.8030          | 54.6634 | 38.2708 | 42.232  | 52.6619   | 142.0    |
  | 0.1058        | 10.0  | 3980 | 0.8057          | 53.8692 | 37.943  | 41.1825 | 51.7243   | 142.0    |
  | 0.0803        | 11.0  | 4378 | 0.8182          | 56.5077 | 41.5916 | 44.1933 | 54.8699   | 142.0    |
  | 0.0599        | 12.0  | 4776 | 0.8261          | 56.9709 | 42.1438 | 45.5351 | 55.0701   | 142.0    |
  | 0.0458        | 13.0  | 5174 | 0.8469          | 56.5208 | 42.0329 | 44.4172 | 54.7958   | 142.0    |
  | 0.0346        | 14.0  | 5572 | 0.8583          | 56.9187 | 42.4072 | 46.1096 | 55.3656   | 142.0    |
  | 0.0346        | 15.0  | 5970 | 0.8653          | 56.503  | 42.047  | 45.8598 | 54.9676   | 141.8519 |
  | 0.0293        | 16.0  | 6368 | 0.8702          | 56.1421 | 41.3514 | 44.5146 | 54.3477   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  