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---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: t5-small-ENG2BASH-NL2BASH-customv1-customv2
  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-customv2

This model is a fine-tuned version of [alexsha/t5-small-ENG2BASH-NL2BASH-customv1](https://huggingface.co/alexsha/t5-small-ENG2BASH-NL2BASH-customv1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3117
- Bleu: 62.6753
- Gen Len: 17.36

## 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   | 40   | 1.3531          | 21.0375 | 12.04   |
| No log        | 2.0   | 80   | 0.6775          | 56.9739 | 16.88   |
| No log        | 3.0   | 120  | 0.5087          | 61.3993 | 17.2    |
| No log        | 4.0   | 160  | 0.4243          | 58.4332 | 17.2    |
| No log        | 5.0   | 200  | 0.3642          | 61.2412 | 17.44   |
| No log        | 6.0   | 240  | 0.3367          | 63.1132 | 17.56   |
| No log        | 7.0   | 280  | 0.3181          | 63.1132 | 17.56   |
| No log        | 8.0   | 320  | 0.3140          | 62.9769 | 17.44   |
| No log        | 9.0   | 360  | 0.3136          | 63.861  | 17.32   |
| No log        | 10.0  | 400  | 0.3117          | 62.6753 | 17.36   |


### Framework versions

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