readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-extraction-cnndm_fs0.01-c
    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-extraction-cnndm_fs0.01-c
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9134
  - Recall: 35.7797
  - Precision: 41.4424
  - F1: 37.1865
  - Gen Len: 18.855
  
  ## 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-06
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 1799
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Recall  | Precision | F1      | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.8241        | 2.27  | 200  | 2.1400          | 15.343  | 40.2687   | 18.9524 | 13.2519 |
  | 2.1335        | 4.55  | 400  | 1.9134          | 35.7797 | 41.4424   | 37.1865 | 18.855  |
  | 1.9806        | 6.82  | 600  | 1.8475          | 34.9684 | 39.4832   | 36.102  | 19.0    |
  | 1.9032        | 9.09  | 800  | 1.8134          | 34.6916 | 38.816    | 35.5849 | 19.0    |
  | 1.8649        | 11.36 | 1000 | 1.7938          | 35.2041 | 39.3235   | 36.079  | 19.0    |
  | 1.8321        | 13.64 | 1200 | 1.7795          | 35.7945 | 39.5656   | 36.5413 | 19.0    |
  | 1.8148        | 15.91 | 1400 | 1.7724          | 35.9774 | 39.8946   | 36.7366 | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  