readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  model-index:
  - name: t5-base-finetuned-summarization-cnn-ver2
    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. -->
  
  # t5-base-finetuned-summarization-cnn-ver2
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7601
  - Bertscore-mean-precision: 0.8926
  - Bertscore-mean-recall: 0.8628
  - Bertscore-mean-f1: 0.8772
  - Bertscore-median-precision: 0.8906
  - Bertscore-median-recall: 0.8600
  - Bertscore-median-f1: 0.8751
  
  ## 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-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
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bertscore-mean-precision | Bertscore-mean-recall | Bertscore-mean-f1 | Bertscore-median-precision | Bertscore-median-recall | Bertscore-median-f1 |
  |:-------------:|:-----:|:-----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:--------------------------:|:-----------------------:|:-------------------:|
  | 1.4581        | 1.0   | 5742  | 1.6800          | 0.8904                   | 0.8615                | 0.8755            | 0.8887                     | 0.8597                  | 0.8737              |
  | 1.2356        | 2.0   | 11484 | 1.7274          | 0.8924                   | 0.8626                | 0.8771            | 0.8911                     | 0.8607                  | 0.8753              |
  | 1.1073        | 3.0   | 17226 | 1.7601          | 0.8926                   | 0.8628                | 0.8772            | 0.8906                     | 0.8600                  | 0.8751              |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  