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# t5-text2sql_v1

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0772
- Rouge2 Precision: 0.8835
- Rouge2 Recall: 0.39
- Rouge2 Fmeasure: 0.5088

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log        | 1.0   | 11   | 1.9420          | 0.0755           | 0.022         | 0.0323          |
| No log        | 2.0   | 22   | 1.2731          | 0.0912           | 0.0263        | 0.039           |
| No log        | 3.0   | 33   | 0.8717          | 0.0993           | 0.0284        | 0.0424          |
| No log        | 4.0   | 44   | 0.5705          | 0.1014           | 0.032         | 0.0464          |
| No log        | 5.0   | 55   | 0.3929          | 0.4151           | 0.1528        | 0.2149          |
| No log        | 6.0   | 66   | 0.2911          | 0.7778           | 0.351         | 0.4594          |
| No log        | 7.0   | 77   | 0.2290          | 0.781            | 0.3305        | 0.4395          |
| No log        | 8.0   | 88   | 0.1995          | 0.7381           | 0.2992        | 0.4018          |
| No log        | 9.0   | 99   | 0.1768          | 0.752            | 0.3147        | 0.4202          |
| No log        | 10.0  | 110  | 0.1554          | 0.7242           | 0.3136        | 0.412           |
| No log        | 11.0  | 121  | 0.1446          | 0.8128           | 0.3583        | 0.4694          |
| No log        | 12.0  | 132  | 0.1337          | 0.8194           | 0.3653        | 0.478           |
| No log        | 13.0  | 143  | 0.1264          | 0.8088           | 0.3564        | 0.4675          |
| No log        | 14.0  | 154  | 0.1170          | 0.8036           | 0.3502        | 0.462           |
| No log        | 15.0  | 165  | 0.1078          | 0.8851           | 0.3981        | 0.5188          |
| No log        | 16.0  | 176  | 0.1046          | 0.8716           | 0.3864        | 0.5054          |
| No log        | 17.0  | 187  | 0.1007          | 0.8753           | 0.3851        | 0.5042          |
| No log        | 18.0  | 198  | 0.0951          | 0.8756           | 0.3941        | 0.5126          |
| No log        | 19.0  | 209  | 0.0928          | 0.8414           | 0.3565        | 0.4708          |
| No log        | 20.0  | 220  | 0.0894          | 0.854            | 0.3642        | 0.4808          |
| No log        | 21.0  | 231  | 0.0863          | 0.8954           | 0.3954        | 0.5168          |
| No log        | 22.0  | 242  | 0.0832          | 0.888            | 0.3931        | 0.5122          |
| No log        | 23.0  | 253  | 0.0828          | 0.8835           | 0.39          | 0.5088          |
| No log        | 24.0  | 264  | 0.0820          | 0.8835           | 0.39          | 0.5088          |
| No log        | 25.0  | 275  | 0.0803          | 0.8835           | 0.39          | 0.5088          |
| No log        | 26.0  | 286  | 0.0792          | 0.8835           | 0.39          | 0.5088          |
| No log        | 27.0  | 297  | 0.0784          | 0.8761           | 0.3886        | 0.5066          |
| No log        | 28.0  | 308  | 0.0775          | 0.8835           | 0.39          | 0.5088          |
| No log        | 29.0  | 319  | 0.0772          | 0.8835           | 0.39          | 0.5088          |
| No log        | 30.0  | 330  | 0.0772          | 0.8835           | 0.39          | 0.5088          |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-text2sql_v1", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-text2sql\_v1
===============


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


* Loss: 0.0772
* Rouge2 Precision: 0.8835
* Rouge2 Recall: 0.39
* Rouge2 Fmeasure: 0.5088


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu113
* Datasets 2.7.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu113
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu113
* Datasets 2.7.1
* Tokenizers 0.13.2
passage: TAGS
#transformers #pytorch #tensorboard #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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu113
* Datasets 2.7.1
* Tokenizers 0.13.2