readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: bart-pt-asqa-ob
    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-pt-asqa-ob
  
  This model is a fine-tuned version of [vblagoje/bart_lfqa](https://huggingface.co/vblagoje/bart_lfqa) on the [ASQA](https://huggingface.co/datasets/din0s/asqa) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6901
  - Rougelsum: 20.7527
  
  ## 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: 5e-06
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|
  | No log        | 1.0   | 355  | 1.6295          | 17.7502   |
  | 1.6407        | 2.0   | 710  | 1.6144          | 18.5897   |
  | 1.4645        | 3.0   | 1065 | 1.6222          | 19.3778   |
  | 1.4645        | 4.0   | 1420 | 1.6522          | 19.6941   |
  | 1.3678        | 5.0   | 1775 | 1.6528          | 20.3110   |
  | 1.2671        | 6.0   | 2130 | 1.6879          | 20.6112   |
  | 1.2671        | 7.0   | 2485 | 1.6901          | 20.7527   |
  
  
  ### Framework versions
  
  - Transformers 4.23.0.dev0
  - Pytorch 1.12.1+cu102
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  