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# t5-large-finetuned-NL2BASH-customv3

This model is a fine-tuned version of [alexsha/t5-large-finetuned-English-to-BASH](https://huggingface.co/alexsha/t5-large-finetuned-English-to-BASH) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7159
- Nl2bash M: 0.8822
- Gen Len: 13.4256

## 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: 3e-05
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Nl2bash M | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| No log        | 1.0   | 387  | 0.7666          | 0.8897    | 13.2314 |
| 0.0177        | 2.0   | 774  | 0.7878          | 0.887     | 13.3512 |
| 0.0188        | 3.0   | 1161 | 0.7580          | 0.8872    | 13.5661 |
| 0.0461        | 4.0   | 1548 | 0.7121          | 0.8846    | 13.3926 |
| 0.0461        | 5.0   | 1935 | 0.7159          | 0.8822    | 13.4256 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.6.1
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-large-finetuned-NL2BASH-customv3", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-large-finetuned-NL2BASH-customv3
===================================


This model is a fine-tuned version of alexsha/t5-large-finetuned-English-to-BASH on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7159
* Nl2bash M: 0.8822
* Gen Len: 13.4256


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: 3e-05
* 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: 5


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.6.1
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* 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: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.6.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* 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: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.6.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* 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: 5### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.6.1
* Tokenizers 0.11.0