readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: NL-RX-Synth-t5-base-finetuned-en-to-regex
    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. -->
  
  # NL-RX-Synth-t5-base-finetuned-en-to-regex
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0255
  - Semantic accuracy: 0.336
  - Syntactic accuracy: 0.286
  - Gen Len: 18.316
  
  ## 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: 0.001
  - 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
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Semantic accuracy | Syntactic accuracy | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:------------------:|:-------:|
  | No log        | 0.18  | 100  | 0.2726          | 0.242             | 0.158              | 18.09   |
  | No log        | 0.36  | 200  | 0.1477          | 0.264             | 0.2                | 18.268  |
  | No log        | 0.53  | 300  | 0.1153          | 0.262             | 0.224              | 18.298  |
  | No log        | 0.71  | 400  | 0.0602          | 0.292             | 0.242              | 18.266  |
  | 0.2992        | 0.89  | 500  | 0.0526          | 0.32              | 0.276              | 18.282  |
  | 0.2992        | 1.07  | 600  | 0.0396          | 0.318             | 0.272              | 18.3    |
  | 0.2992        | 1.24  | 700  | 0.0326          | 0.318             | 0.286              | 18.33   |
  | 0.2992        | 1.42  | 800  | 0.0322          | 0.326             | 0.28               | 18.314  |
  | 0.2992        | 1.6   | 900  | 0.0267          | 0.326             | 0.278              | 18.328  |
  | 0.0383        | 1.78  | 1000 | 0.0255          | 0.336             | 0.286              | 18.316  |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  