readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-extraction-cnndm_fs0.05-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_fs0.05-c
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8827
  - Recall: 35.7635
  - Precision: 41.5969
  - F1: 37.3657
  - Gen Len: 18.9954
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.807         | 0.46  | 200  | 2.1329          | 13.6873 | 33.1264   | 16.8464 | 16.3902 |
  | 2.1128        | 0.92  | 400  | 1.8827          | 35.7635 | 41.5969   | 37.3657 | 18.9954 |
  | 1.9542        | 1.38  | 600  | 1.8183          | 34.5118 | 39.6272   | 35.8056 | 18.9832 |
  | 1.8931        | 1.83  | 800  | 1.7703          | 34.7482 | 39.7998   | 36.0141 | 18.9878 |
  | 1.8535        | 2.29  | 1000 | 1.7436          | 34.9113 | 40.13     | 36.2079 | 18.9954 |
  | 1.8016        | 2.75  | 1200 | 1.7196          | 35.2072 | 40.209    | 36.3859 | 18.997  |
  | 1.7822        | 3.21  | 1400 | 1.6997          | 35.2425 | 40.2356   | 36.4166 | 18.997  |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  