readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-small-med-term-conditional-masking
    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-small-med-term-conditional-masking
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6808
  - Rouge2 Precision: 0.6855
  - Rouge2 Recall: 0.486
  - Rouge2 Fmeasure: 0.5507
  
  ## 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: 2e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 0.9303        | 1.0   | 15827  | 0.8262          | 0.6603           | 0.4698        | 0.5318          |
  | 0.8677        | 2.0   | 31654  | 0.7679          | 0.6695           | 0.4762        | 0.539           |
  | 0.8315        | 3.0   | 47481  | 0.7393          | 0.6741           | 0.4783        | 0.5418          |
  | 0.7999        | 4.0   | 63308  | 0.7194          | 0.6774           | 0.4811        | 0.5448          |
  | 0.7746        | 5.0   | 79135  | 0.7059          | 0.6804           | 0.4815        | 0.5459          |
  | 0.7785        | 6.0   | 94962  | 0.6958          | 0.6827           | 0.4841        | 0.5485          |
  | 0.7592        | 7.0   | 110789 | 0.6893          | 0.6841           | 0.4849        | 0.5494          |
  | 0.745         | 8.0   | 126616 | 0.6849          | 0.6846           | 0.4852        | 0.5498          |
  | 0.7443        | 9.0   | 142443 | 0.6818          | 0.6854           | 0.4865        | 0.551           |
  | 0.7417        | 10.0  | 158270 | 0.6808          | 0.6855           | 0.486         | 0.5507          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  