readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-cnn_dailymail-finetuned-roundup
    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-cnn_dailymail-finetuned-roundup
  
  This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9488
  - Rouge1: 55.4754
  - Rouge2: 39.1074
  - Rougel: 40.822
  - Rougelsum: 47.3045
  - Gen Len: 126.7778
  
  ## 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | 1.8482        | 1.0   | 795   | 1.3177          | 51.1349 | 32.0791 | 34.4191 | 41.2001   | 127.0    |
  | 1.362         | 2.0   | 1590  | 1.1975          | 52.1955 | 33.7858 | 36.2998 | 42.5368   | 127.0    |
  | 1.2847        | 3.0   | 2385  | 1.1299          | 53.3694 | 35.9817 | 39.2437 | 45.2062   | 127.0    |
  | 1.1673        | 4.0   | 3180  | 1.0903          | 53.3629 | 35.173  | 37.7775 | 44.3446   | 126.8889 |
  | 1.0943        | 5.0   | 3975  | 1.0525          | 54.6538 | 37.3115 | 39.5883 | 46.8043   | 127.0    |
  | 1.0615        | 6.0   | 4770  | 1.0317          | 54.6794 | 36.7147 | 39.5731 | 45.8527   | 127.0    |
  | 0.993         | 7.0   | 5565  | 1.0144          | 55.2425 | 38.3984 | 41.1723 | 47.266    | 126.8704 |
  | 0.9705        | 8.0   | 6360  | 0.9993          | 55.3351 | 38.3237 | 40.4765 | 47.3272   | 127.0    |
  | 0.9266        | 9.0   | 7155  | 0.9864          | 55.174  | 38.0535 | 40.3484 | 46.7058   | 126.0926 |
  | 0.9181        | 10.0  | 7950  | 0.9713          | 54.822  | 37.8024 | 40.0583 | 46.4962   | 126.5    |
  | 0.9053        | 11.0  | 8745  | 0.9690          | 55.6235 | 38.9253 | 40.6261 | 47.1602   | 127.0    |
  | 0.8513        | 12.0  | 9540  | 0.9614          | 55.3525 | 38.9343 | 40.4011 | 46.9631   | 127.0    |
  | 0.8436        | 13.0  | 10335 | 0.9565          | 56.1316 | 39.5794 | 41.4653 | 47.7626   | 127.0    |
  | 0.8343        | 14.0  | 11130 | 0.9522          | 55.7155 | 38.9484 | 40.968  | 47.0273   | 126.7778 |
  | 0.8308        | 15.0  | 11925 | 0.9502          | 55.7195 | 39.1268 | 40.7967 | 47.1869   | 127.0    |
  | 0.8296        | 16.0  | 12720 | 0.9488          | 55.4754 | 39.1074 | 40.822  | 47.3045   | 126.7778 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  