readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-extraction-cnndm_fs0.1-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_fs0.1-c
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7561
  - Recall: 35.1408
  - Precision: 43.9868
  - F1: 37.6193
  - Gen Len: 18.9893
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.769         | 0.23  | 200  | 2.0599          | 16.0029 | 43.3146   | 19.8284 | 14.0853 |
  | 2.0953        | 0.46  | 400  | 1.8269          | 34.8962 | 43.655    | 37.3268 | 18.965  |
  | 1.9314        | 0.69  | 600  | 1.7561          | 35.1408 | 43.9868   | 37.6193 | 18.9893 |
  | 1.8726        | 0.92  | 800  | 1.7092          | 34.4843 | 42.7967   | 36.7767 | 18.981  |
  | 1.8204        | 1.15  | 1000 | 1.6813          | 34.297  | 42.1293   | 36.4464 | 18.9901 |
  | 1.7835        | 1.38  | 1200 | 1.6515          | 34.4798 | 42.7495   | 36.7933 | 18.9886 |
  | 1.755         | 1.61  | 1400 | 1.6363          | 34.3779 | 42.4339   | 36.58   | 18.997  |
  | 1.7499        | 1.83  | 1600 | 1.6219          | 34.3912 | 42.5407   | 36.6334 | 18.9855 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  