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# gpt2_finetuned_with_schema

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the wikisql dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1059
- eval_runtime: 62.0026
- eval_samples_per_second: 135.817
- eval_steps_per_second: 33.966
- epoch: 2.0
- step: 3522

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["wikisql"], "model-index": [{"name": "gpt2_finetuned_with_schema", "results": []}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:wikisql license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-wikisql #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# gpt2_finetuned_with_schema

This model is a fine-tuned version of gpt2 on the wikisql dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1059
- eval_runtime: 62.0026
- eval_samples_per_second: 135.817
- eval_steps_per_second: 33.966
- epoch: 2.0
- step: 3522

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# gpt2_finetuned_with_schema

This model is a fine-tuned version of gpt2 on the wikisql dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1059
- eval_runtime: 62.0026
- eval_samples_per_second: 135.817
- eval_steps_per_second: 33.966
- epoch: 2.0
- step: 3522 ## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-wikisql #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # gpt2_finetuned_with_schema

This model is a fine-tuned version of gpt2 on the wikisql dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1059
- eval_runtime: 62.0026
- eval_samples_per_second: 135.817
- eval_steps_per_second: 33.966
- epoch: 2.0
- step: 3522 ## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-wikisql #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# gpt2_finetuned_with_schema

This model is a fine-tuned version of gpt2 on the wikisql dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1059
- eval_runtime: 62.0026
- eval_samples_per_second: 135.817
- eval_steps_per_second: 33.966
- epoch: 2.0
- step: 3522## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3