readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: QAGP_final
    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. -->
  
  # QAGP_final
  
  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2268
  
  ## 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: 0.0001
  - 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
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 1.8819        | 0.16  | 1000  | 1.4078          |
  | 1.4792        | 0.33  | 2000  | 1.3247          |
  | 1.4406        | 0.49  | 3000  | 1.2776          |
  | 1.4286        | 0.66  | 4000  | 1.2464          |
  | 1.3776        | 0.82  | 5000  | 1.2476          |
  | 1.3361        | 0.98  | 6000  | 1.2191          |
  | 1.0983        | 1.15  | 7000  | 1.2404          |
  | 1.0992        | 1.31  | 8000  | 1.2255          |
  | 1.064         | 1.48  | 9000  | 1.2169          |
  | 1.0771        | 1.64  | 10000 | 1.2077          |
  | 1.0484        | 1.8   | 11000 | 1.2057          |
  | 1.0428        | 1.97  | 12000 | 1.1912          |
  | 0.8319        | 2.13  | 13000 | 1.2383          |
  | 0.8801        | 2.3   | 14000 | 1.2271          |
  | 0.8215        | 2.46  | 15000 | 1.2353          |
  | 0.8407        | 2.63  | 16000 | 1.2328          |
  | 0.8449        | 2.79  | 17000 | 1.2258          |
  | 0.8283        | 2.95  | 18000 | 1.2268          |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Tokenizers 0.12.1
  