readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - cnn_dailymail
  model-index:
  - name: t5-v1_1-small-finetuned-summarization-cnn-ver1
    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-v1_1-small-finetuned-summarization-cnn-ver1
  
  This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the cnn_dailymail dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7467
  - Bertscore-mean-precision: 0.8764
  - Bertscore-mean-recall: 0.8519
  - Bertscore-mean-f1: 0.8639
  - Bertscore-median-precision: 0.8746
  - Bertscore-median-recall: 0.8518
  - Bertscore-median-f1: 0.8632
  
  ## 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: 4e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:--------------------------:|:-----------------------:|:-------------------:|
  | 4.6845        | 1.0   | 718  | 2.9003          | 0.8698                   | 0.8456                | 0.8574            | 0.8693                     | 0.8445                  | 0.8570              |
  | 3.7925        | 2.0   | 1436 | 2.7654          | 0.8765                   | 0.8519                | 0.8639            | 0.8745                     | 0.8512                  | 0.8629              |
  | 3.6332        | 3.0   | 2154 | 2.7467          | 0.8764                   | 0.8519                | 0.8639            | 0.8746                     | 0.8518                  | 0.8632              |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  