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# t5-text2sql

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: 0.1611
- Rouge2 Precision: 0.8631
- Rouge2 Recall: 0.2595
- Rouge2 Fmeasure: 0.3674

## 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   | 1.8867          | 0.0              | 0.0           | 0.0             |
| No log        | 2.0   | 22   | 0.9658          | 0.0119           | 0.0015        | 0.0027          |
| No log        | 3.0   | 33   | 0.6477          | 0.0468           | 0.0078        | 0.0135          |
| No log        | 4.0   | 44   | 0.4617          | 0.4251           | 0.14          | 0.1943          |
| No log        | 5.0   | 55   | 0.3669          | 0.6403           | 0.2091        | 0.2937          |
| No log        | 6.0   | 66   | 0.3084          | 0.7085           | 0.2446        | 0.3393          |
| No log        | 7.0   | 77   | 0.2788          | 0.7282           | 0.2246        | 0.3175          |
| No log        | 8.0   | 88   | 0.2549          | 0.7593           | 0.2346        | 0.332           |
| No log        | 9.0   | 99   | 0.2368          | 0.7738           | 0.2367        | 0.3348          |
| No log        | 10.0  | 110  | 0.2322          | 0.7889           | 0.2388        | 0.3393          |
| No log        | 11.0  | 121  | 0.2151          | 0.8056           | 0.2419        | 0.3452          |
| No log        | 12.0  | 132  | 0.2067          | 0.7996           | 0.2371        | 0.3382          |
| No log        | 13.0  | 143  | 0.2003          | 0.7943           | 0.2365        | 0.3364          |
| No log        | 14.0  | 154  | 0.1899          | 0.8204           | 0.244         | 0.3477          |
| No log        | 15.0  | 165  | 0.1869          | 0.8309           | 0.2454        | 0.3502          |
| No log        | 16.0  | 176  | 0.1826          | 0.8309           | 0.2454        | 0.3502          |
| No log        | 17.0  | 187  | 0.1797          | 0.8252           | 0.245         | 0.3488          |
| No log        | 18.0  | 198  | 0.1749          | 0.8353           | 0.2479        | 0.3535          |
| No log        | 19.0  | 209  | 0.1726          | 0.8393           | 0.2508        | 0.3566          |
| No log        | 20.0  | 220  | 0.1716          | 0.8373           | 0.2475        | 0.3538          |
| No log        | 21.0  | 231  | 0.1695          | 0.8472           | 0.2489        | 0.3553          |
| No log        | 22.0  | 242  | 0.1693          | 0.8472           | 0.2519        | 0.3589          |
| No log        | 23.0  | 253  | 0.1685          | 0.877            | 0.271         | 0.3808          |
| No log        | 24.0  | 264  | 0.1668          | 0.8552           | 0.2598        | 0.3666          |
| No log        | 25.0  | 275  | 0.1641          | 0.8552           | 0.252         | 0.3591          |
| No log        | 26.0  | 286  | 0.1628          | 0.8671           | 0.2598        | 0.3683          |
| No log        | 27.0  | 297  | 0.1617          | 0.8631           | 0.2595        | 0.3674          |
| No log        | 28.0  | 308  | 0.1611          | 0.8631           | 0.2595        | 0.3674          |
| No log        | 29.0  | 319  | 0.1611          | 0.8631           | 0.2595        | 0.3674          |
| No log        | 30.0  | 330  | 0.1611          | 0.8631           | 0.2595        | 0.3674          |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-text2sql", "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
===========


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


* Loss: 0.1611
* Rouge2 Precision: 0.8631
* Rouge2 Recall: 0.2595
* Rouge2 Fmeasure: 0.3674


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 4.21.3
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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 4.21.3
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
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 4.21.3
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
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 4.21.3
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1