readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-xsum-whole_summary_chatGPT_and_tweetsum
    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. -->
  
  # pegasus-xsum-whole_summary_chatGPT_and_tweetsum
  
  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: 2.4139
  - Rouge1: 27.4412
  - Rouge2: 10.8393
  - Rougel: 25.1988
  - Rougelsum: 25.2193
  - Gen Len: 14.3333
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 381  | 2.5524          | 26.025  | 9.5118  | 22.8243 | 22.8505   | 15.8095 |
  | 2.9387        | 2.0   | 762  | 2.4394          | 29.4773 | 11.7365 | 27.6403 | 27.7766   | 15.4286 |
  | 2.2822        | 3.0   | 1143 | 2.4139          | 27.4412 | 10.8393 | 25.1988 | 25.2193   | 14.3333 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  