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# sql-gen-join-opt

This model is a fine-tuned version of [Salesforce/codegen-350M-multi](https://huggingface.co/Salesforce/codegen-350M-multi) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0383

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 109  | 0.0609          |
| No log        | 2.0   | 218  | 0.0450          |
| No log        | 2.99  | 327  | 0.0383          |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.12.1+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "model-index": [{"name": "sql-gen-join-opt", "results": []}]}
transformers pytorch codegen text-generation generated_from_trainer license:bsd-3-clause autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #codegen #text-generation #generated_from_trainer #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #region-us 

sql-gen-join-opt
================


This model is a fine-tuned version of Salesforce/codegen-350M-multi on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0383


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: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #codegen #text-generation #generated_from_trainer #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #codegen #text-generation #generated_from_trainer #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 1.12.1+cu113
* Datasets 2.10.1
* Tokenizers 0.13.2