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# output_tiny

This model is a fine-tuned version of [gpt2_tiny_random](https://huggingface.co/gpt2_tiny_random) on the wikitext wikitext-103-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3359
- Accuracy: 0.2133

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 50000

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "datasets": ["wikitext"], "metrics": ["accuracy"], "model-index": [{"name": "output_tiny", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "wikitext wikitext-103-v1", "type": "wikitext", "args": "wikitext-103-v1"}, "metrics": [{"type": "accuracy", "value": 0.2132901596611274, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:wikitext model-index autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-wikitext #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 




# output_tiny

This model is a fine-tuned version of gpt2_tiny_random on the wikitext wikitext-103-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3359
- Accuracy: 0.2133

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 50000

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2

# output_tiny

This model is a fine-tuned version of gpt2_tiny_random on the wikitext wikitext-103-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3359
- Accuracy: 0.2133 ## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 50000 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-wikitext #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # output_tiny

This model is a fine-tuned version of gpt2_tiny_random on the wikitext wikitext-103-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3359
- Accuracy: 0.2133 ## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 50000 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-wikitext #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
# output_tiny

This model is a fine-tuned version of gpt2_tiny_random on the wikitext wikitext-103-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3359
- Accuracy: 0.2133## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 50000### Training results### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2