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# t5-large-finetuned-English-to-BASH

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7646
- Nl2bash M: 0.7822
- Gen Len: 14.4665

## 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: 4e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Nl2bash M | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.2312        | 1.0   | 561  | 0.6370          | 0.7743    | 14.4202 |
| 0.1836        | 2.0   | 1122 | 0.6767          | 0.7782    | 14.4585 |
| 0.1445        | 3.0   | 1683 | 0.7171          | 0.7805    | 14.3586 |
| 0.1263        | 4.0   | 2244 | 0.7457          | 0.78      | 14.479  |
| 0.1092        | 5.0   | 2805 | 0.7646          | 0.7822    | 14.4665 |


### Framework versions

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

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

t5-large-finetuned-English-to-BASH
==================================


This model is a fine-tuned version of t5-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7646
* Nl2bash M: 0.7822
* Gen Len: 14.4665


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: 4e-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: 5


### Training results



### Framework versions


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



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-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: 5 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-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: 5 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4e-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: 5### Training results### Framework versions


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