readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-small-mlm-pubmed-45
    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-mlm-pubmed-45
  
  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: 1.6395
  - Rouge2 Precision: 0.3383
  - Rouge2 Recall: 0.2424
  - Rouge2 Fmeasure: 0.2753
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 2.519         | 0.75  | 500  | 1.9659          | 0.3178           | 0.1888        | 0.2299          |
  | 2.169         | 1.51  | 1000 | 1.8450          | 0.3256           | 0.2138        | 0.25            |
  | 2.0796        | 2.26  | 1500 | 1.7900          | 0.3368           | 0.2265        | 0.2636          |
  | 1.9978        | 3.02  | 2000 | 1.7553          | 0.3427           | 0.234         | 0.2709          |
  | 1.9686        | 3.77  | 2500 | 1.7172          | 0.3356           | 0.2347        | 0.2692          |
  | 1.9142        | 4.52  | 3000 | 1.6986          | 0.3358           | 0.238         | 0.2715          |
  | 1.921         | 5.28  | 3500 | 1.6770          | 0.3349           | 0.2379        | 0.2709          |
  | 1.8848        | 6.03  | 4000 | 1.6683          | 0.3346           | 0.2379        | 0.2708          |
  | 1.8674        | 6.79  | 4500 | 1.6606          | 0.3388           | 0.2419        | 0.2752          |
  | 1.8606        | 7.54  | 5000 | 1.6514          | 0.3379           | 0.2409        | 0.274           |
  | 1.8515        | 8.3   | 5500 | 1.6438          | 0.3356           | 0.2407        | 0.2731          |
  | 1.8403        | 9.05  | 6000 | 1.6401          | 0.3367           | 0.2421        | 0.2744          |
  | 1.8411        | 9.8   | 6500 | 1.6395          | 0.3383           | 0.2424        | 0.2753          |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  