readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-extraction-cnndm_fs0.2-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_fs0.2-c
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7632
  - Recall: 35.3211
  - Precision: 44.7184
  - F1: 37.9638
  - Gen Len: 18.9772
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.869         | 0.11  | 200  | 2.1451          | 5.0936  | 24.6632   | 7.5994  | 18.7768 |
  | 2.1528        | 0.23  | 400  | 1.8487          | 34.4362 | 43.9397   | 36.9118 | 18.9848 |
  | 1.9838        | 0.34  | 600  | 1.7632          | 35.3211 | 44.7184   | 37.9638 | 18.9772 |
  | 1.9177        | 0.46  | 800  | 1.7159          | 35.2238 | 43.6081   | 37.5322 | 18.9939 |
  | 1.866         | 0.57  | 1000 | 1.6831          | 34.9749 | 43.3927   | 37.2946 | 18.9924 |
  | 1.8292        | 0.69  | 1200 | 1.6564          | 35.1338 | 43.3687   | 37.3903 | 18.9954 |
  | 1.8132        | 0.8   | 1400 | 1.6331          | 35.1356 | 43.4627   | 37.3786 | 18.9954 |
  | 1.7891        | 0.92  | 1600 | 1.6194          | 35.3715 | 44.0317   | 37.7205 | 18.9855 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  