readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-finetuned-roundup-4-8
    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-large-cnn-finetuned-roundup-4-8
  
  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7882
  - Rouge1: 54.2292
  - Rouge2: 37.3874
  - Rougel: 40.3261
  - Rougelsum: 52.2155
  - Gen Len: 141.8889
  
  ## 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: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 398  | 0.9442          | 53.1634 | 33.7744 | 35.5688 | 50.7523   | 142.0    |
  | 1.1285        | 2.0   | 796  | 0.8305          | 54.0713 | 35.7079 | 37.5147 | 51.6285   | 142.0    |
  | 0.6796        | 3.0   | 1194 | 0.7735          | 52.6656 | 34.0198 | 36.8075 | 50.1502   | 142.0    |
  | 0.4572        | 4.0   | 1592 | 0.7759          | 53.6269 | 35.4308 | 38.3735 | 51.1369   | 141.7222 |
  | 0.4572        | 5.0   | 1990 | 0.7527          | 54.4206 | 36.0907 | 38.0818 | 51.7885   | 142.0    |
  | 0.3171        | 6.0   | 2388 | 0.7755          | 54.9642 | 38.0459 | 41.6383 | 52.8847   | 142.0    |
  | 0.2269        | 7.0   | 2786 | 0.7801          | 54.1637 | 35.9853 | 39.5262 | 51.6562   | 142.0    |
  | 0.1686        | 8.0   | 3184 | 0.7882          | 54.2292 | 37.3874 | 40.3261 | 52.2155   | 141.8889 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  