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# gpt2-small-mt

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the MapTask dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0708
- Accuracy: 0.5562

## Model description

More details soon.

## Intended uses & limitations

More details soon.

## Training and evaluation data

More details soon.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results



### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0

{"language": ["en"], "metrics": ["accuracy"], "model-index": [{"name": "gpt2-small-mt", "results": []}]}
transformers pytorch gpt2 text-generation en autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# gpt2-small-mt

This model is a fine-tuned version of gpt2 on the MapTask dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0708
- Accuracy: 0.5562

## Model description

More details soon.

## Intended uses & limitations

More details soon.

## Training and evaluation data

More details soon.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results



### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0

# gpt2-small-mt

This model is a fine-tuned version of gpt2 on the MapTask dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0708
- Accuracy: 0.5562 ## Model description

More details soon. ## Intended uses & limitations

More details soon. ## Training and evaluation data

More details soon. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0 ### Training results ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0
TAGS
#transformers #pytorch #gpt2 #text-generation #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # gpt2-small-mt

This model is a fine-tuned version of gpt2 on the MapTask dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0708
- Accuracy: 0.5562 ## Model description

More details soon. ## Intended uses & limitations

More details soon. ## Training and evaluation data

More details soon. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0 ### Training results ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0