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---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: t5-small-ENG2BASH-NL2BASH-customv1
  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-ENG2BASH-NL2BASH-customv1

This model is a fine-tuned version of [alexsha/t5-small-ENG2BASH-NL2BASH](https://huggingface.co/alexsha/t5-small-ENG2BASH-NL2BASH) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2460
- Bleu: 89.1258
- Gen Len: 6.4872

## 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: 0.0002
- train_batch_size: 5
- eval_batch_size: 5
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 63   | 0.9255          | 8.9812  | 6.7179  |
| No log        | 2.0   | 126  | 0.5406          | 52.1648 | 7.0256  |
| No log        | 3.0   | 189  | 0.3841          | 61.0328 | 7.5897  |
| No log        | 4.0   | 252  | 0.2745          | 65.7791 | 7.641   |
| No log        | 5.0   | 315  | 0.2461          | 83.3    | 6.5641  |
| No log        | 6.0   | 378  | 0.2582          | 84.9958 | 6.7436  |
| No log        | 7.0   | 441  | 0.2703          | 85.5359 | 6.3333  |
| 0.5161        | 8.0   | 504  | 0.2527          | 86.893  | 6.7179  |
| 0.5161        | 9.0   | 567  | 0.2471          | 88.5593 | 6.5641  |
| 0.5161        | 10.0  | 630  | 0.2460          | 89.1258 | 6.4872  |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2