readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: KB13-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. -->
  
  # KB13-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: 0.4785
  - Semantic accuracy: 0.3902
  - Syntactic accuracy: 0.3171
  - Gen Len: 15.2927
  
  ## 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        | 2.13  | 100  | 0.7159          | 0.122             | 0.0976             | 15.2439 |
  | No log        | 4.26  | 200  | 0.4649          | 0.2683            | 0.2195             | 15.0488 |
  | No log        | 6.38  | 300  | 0.3749          | 0.4146            | 0.3415             | 15.3659 |
  | No log        | 8.51  | 400  | 0.4155          | 0.3902            | 0.2927             | 15.0976 |
  | 0.5191        | 10.64 | 500  | 0.4148          | 0.3902            | 0.2927             | 15.7561 |
  | 0.5191        | 12.77 | 600  | 0.4010          | 0.439             | 0.3415             | 15.3902 |
  | 0.5191        | 14.89 | 700  | 0.4429          | 0.3902            | 0.3171             | 15.3659 |
  | 0.5191        | 17.02 | 800  | 0.4607          | 0.3902            | 0.3415             | 15.561  |
  | 0.5191        | 19.15 | 900  | 0.4629          | 0.3902            | 0.3171             | 15.122  |
  | 0.0518        | 21.28 | 1000 | 0.4785          | 0.3902            | 0.3171             | 15.2927 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  