readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: bart_large_paraphrase_generator_en_de_v2
    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_paraphrase_generator_en_de_v2
  
  This model was trained from scratch on an unknown dataset.
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  {'eval_loss': 0.9200083613395691, 'eval_score': 49.97448884411352, 'eval_counts': [100712, 72963, 57055, 41578], 'eval_totals': [133837, 130839, 127841, 124843], 'eval_precisions': [75.24974409169363, 55.76548276889918, 44.6296571522438, 33.30423011302196], 'eval_bp': 1.0, 'eval_sys_len': 133837, 'eval_ref_len': 130883, 'eval_runtime': 138.6871, 'eval_samples_per_second': 21.617, 'eval_steps_per_second': 0.678}
  
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 4
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - total_eval_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.11.0a0+bfe5ad2
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  