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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- nl2bash_m
model-index:
- name: t5-v1_1-base-finetuned-English-to-BASH
results: []
---
# t5-v1_1-base-finetuned-English-to-BASH
Created by: [Josh Shih](https://huggingface.co/Josh98), [Alex Sha](https://huggingface.co/alexsha), [Kevin Um](https://huggingface.co/kevinum) for EEP 596 - Natural Language Processing at University of Washington (Seattle).
This model is a fine-tuned version of [google/t5-v1_1-base](https://huggingface.co/google/t5-v1_1-base) on a more balanced iteration of the [NL2BASH](https://github.com/TellinaTool/nl2bash/tree/master/data) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7958
- Nl2bash M: 0.6179
- Gen Len: 14.0821
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
This model was trained and evaluated using a custom iteration of [NL2BASH](https://github.com/TellinaTool/nl2bash/tree/master/data). The original NL2BASH dataset contains a large class imbalance with too many bash commands which begin with 'find'.
A maximum threshold was set to remove text/BASH pairs which exceeded the threshold, and [GPT-3](https://openai.com/blog/gpt-3-apps/) API was used to generate text/BASH pairs for those below the threshold.
~5500 original text/BASH pairs and ~5700 generated text/BASH pairs were used, giving a total of ~11200 lines of text/BASH pairs. Shown below is the class distribution for the top-5 commands.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Nl2bash M | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 4.7401 | 1.0 | 561 | 1.6374 | 0.258 | 12.9715 |
| 1.9636 | 2.0 | 1122 | 1.2574 | 0.345 | 14.4728 |
| 1.5349 | 3.0 | 1683 | 1.0844 | 0.3873 | 14.5727 |
| 1.3565 | 4.0 | 2244 | 0.9777 | 0.4705 | 14.3506 |
| 1.2006 | 5.0 | 2805 | 0.8995 | 0.5536 | 14.2159 |
| 1.0931 | 6.0 | 3366 | 0.8622 | 0.5848 | 14.0883 |
| 1.0008 | 7.0 | 3927 | 0.8261 | 0.603 | 14.1401 |
| 0.952 | 8.0 | 4488 | 0.8146 | 0.6145 | 13.9322 |
| 0.8829 | 9.0 | 5049 | 0.8013 | 0.6185 | 13.9715 |
| 0.8657 | 10.0 | 5610 | 0.7958 | 0.6179 | 14.0821 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
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