readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: t5-small-finetuned-English-to-BASH
    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-finetuned-English-to-BASH
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the [nl2bash](https://github.com/TellinaTool/nl2bash) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6779
  - Bleu: 14.1023
  - Gen Len: 17.9627
  
  ## 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 | Bleu    | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 2.7096        | 1.0   | 631  | 2.2207          | 12.045  | 18.8049 |
  | 2.3956        | 2.0   | 1262 | 2.0190          | 13.0337 | 18.5385 |
  | 2.2417        | 3.0   | 1893 | 1.9048          | 13.2245 | 18.502  |
  | 2.0624        | 4.0   | 2524 | 1.8337          | 13.2271 | 18.4227 |
  | 1.9994        | 5.0   | 3155 | 1.7764          | 13.7544 | 18.3037 |
  | 1.9592        | 6.0   | 3786 | 1.7381          | 13.5463 | 18.2078 |
  | 1.9189        | 7.0   | 4417 | 1.7104          | 13.9351 | 18.1523 |
  | 1.8743        | 8.0   | 5048 | 1.6927          | 14.0911 | 17.9944 |
  | 1.8628        | 9.0   | 5679 | 1.6820          | 14.2007 | 17.9175 |
  | 1.8468        | 10.0  | 6310 | 1.6779          | 14.1023 | 17.9627 |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  