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# t5-small-finetuned-wikisql

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1165
- Rouge2 Precision: 0.8267
- Rouge2 Recall: 0.7345
- Rouge2 Fmeasure: 0.7706

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.2196        | 1.0   | 3569  | 0.1709          | 0.7843           | 0.6963        | 0.7307          |
| 0.1767        | 2.0   | 7138  | 0.1480          | 0.8031           | 0.7118        | 0.7477          |
| 0.1614        | 3.0   | 10707 | 0.1353          | 0.8115           | 0.72          | 0.7559          |
| 0.148         | 4.0   | 14276 | 0.1287          | 0.8165           | 0.7244        | 0.7604          |
| 0.1406        | 5.0   | 17845 | 0.1242          | 0.8207           | 0.7283        | 0.7646          |
| 0.1337        | 6.0   | 21414 | 0.1209          | 0.8238           | 0.7313        | 0.7676          |
| 0.1296        | 7.0   | 24983 | 0.1193          | 0.8252           | 0.7329        | 0.7691          |
| 0.1271        | 8.0   | 28552 | 0.1177          | 0.825            | 0.7329        | 0.7691          |
| 0.1222        | 9.0   | 32121 | 0.1167          | 0.8262           | 0.7341        | 0.7702          |
| 0.1229        | 10.0  | 35690 | 0.1165          | 0.8267           | 0.7345        | 0.7706          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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


This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1165
* Rouge2 Precision: 0.8267
* Rouge2 Recall: 0.7345
* Rouge2 Fmeasure: 0.7706


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: 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: 10


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* 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 #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* 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 #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2