readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-extraction-cnndm_fs0.02-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_fs0.02-c
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8400
  - Recall: 35.4852
  - Precision: 40.9499
  - F1: 36.9238
  - Gen Len: 19.0
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.7966        | 1.14  | 200  | 2.0568          | 17.0907 | 45.1725   | 21.4724 | 12.7061 |
  | 2.1271        | 2.29  | 400  | 1.8400          | 35.4852 | 40.9499   | 36.9238 | 19.0    |
  | 1.9831        | 3.43  | 600  | 1.7756          | 35.0259 | 39.8685   | 36.1824 | 18.9962 |
  | 1.9025        | 4.57  | 800  | 1.7365          | 34.9077 | 39.2092   | 35.8205 | 19.0    |
  | 1.8564        | 5.71  | 1000 | 1.7075          | 33.8282 | 38.141    | 34.765  | 19.0    |
  | 1.8164        | 6.86  | 1200 | 1.6898          | 34.6927 | 38.999    | 35.5568 | 19.0    |
  | 1.7929        | 8.0   | 1400 | 1.6753          | 34.9922 | 39.2711   | 35.8318 | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  