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# t5-text2sql_v3

This model is a fine-tuned version of [mousaazari/t5-text2sql_v1](https://huggingface.co/mousaazari/t5-text2sql_v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1501
- Rouge2 Precision: 0.6088
- Rouge2 Recall: 0.3597
- Rouge2 Fmeasure: 0.4201

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log        | 1.0   | 430  | 0.3126          | 0.3937           | 0.2301        | 0.2679          |
| 0.4851        | 2.0   | 860  | 0.2583          | 0.4656           | 0.2854        | 0.3289          |
| 0.3271        | 3.0   | 1290 | 0.2256          | 0.4858           | 0.2875        | 0.3337          |
| 0.2696        | 4.0   | 1720 | 0.2075          | 0.5193           | 0.3127        | 0.3614          |
| 0.2376        | 5.0   | 2150 | 0.1937          | 0.5387           | 0.3258        | 0.3773          |
| 0.2072        | 6.0   | 2580 | 0.1839          | 0.5524           | 0.3344        | 0.3876          |
| 0.1875        | 7.0   | 3010 | 0.1752          | 0.5644           | 0.3333        | 0.3882          |
| 0.1875        | 8.0   | 3440 | 0.1704          | 0.5751           | 0.3426        | 0.399           |
| 0.1736        | 9.0   | 3870 | 0.1653          | 0.5821           | 0.3458        | 0.4027          |
| 0.1585        | 10.0  | 4300 | 0.1603          | 0.5841           | 0.3435        | 0.4013          |
| 0.1498        | 11.0  | 4730 | 0.1576          | 0.5905           | 0.3535        | 0.4103          |
| 0.1427        | 12.0  | 5160 | 0.1548          | 0.6031           | 0.3533        | 0.4135          |
| 0.1342        | 13.0  | 5590 | 0.1541          | 0.5976           | 0.3519        | 0.411           |
| 0.1294        | 14.0  | 6020 | 0.1534          | 0.6058           | 0.3549        | 0.4161          |
| 0.1294        | 15.0  | 6450 | 0.1518          | 0.6117           | 0.3593        | 0.4203          |
| 0.1239        | 16.0  | 6880 | 0.1509          | 0.61             | 0.3597        | 0.4202          |
| 0.1198        | 17.0  | 7310 | 0.1508          | 0.6076           | 0.3588        | 0.4195          |
| 0.1147        | 18.0  | 7740 | 0.1503          | 0.6139           | 0.3607        | 0.4219          |
| 0.1155        | 19.0  | 8170 | 0.1503          | 0.6092           | 0.3597        | 0.4201          |
| 0.1115        | 20.0  | 8600 | 0.1501          | 0.6088           | 0.3597        | 0.4201          |


### Framework versions

- Transformers 4.26.0
- Pytorch 2.0.0+cu118
- Datasets 2.8.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-text2sql_v3", "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\_v3
===============


This model is a fine-tuned version of mousaazari/t5-text2sql\_v1 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1501
* Rouge2 Precision: 0.6088
* Rouge2 Recall: 0.3597
* Rouge2 Fmeasure: 0.4201


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: 20


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu118
* Datasets 2.8.0
* Tokenizers 0.13.3



### 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: 20 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu118
* Datasets 2.8.0
* Tokenizers 0.13.3
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: 20 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 2.0.0+cu118
* Datasets 2.8.0
* Tokenizers 0.13.3