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# german-poetry-gpt2

This model is a fine-tuned version of [dbmdz/german-gpt2](https://huggingface.co/dbmdz/german-gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.8196
- eval_runtime: 43.8543
- eval_samples_per_second: 86.993
- eval_steps_per_second: 5.45
- epoch: 9.0
- step: 11520

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 22

### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "german-poetry-gpt2", "results": []}]}
transformers pytorch tensorboard safetensors gpt2 text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# german-poetry-gpt2

This model is a fine-tuned version of dbmdz/german-gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.8196
- eval_runtime: 43.8543
- eval_samples_per_second: 86.993
- eval_steps_per_second: 5.45
- epoch: 9.0
- step: 11520

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 22

### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1

# german-poetry-gpt2

This model is a fine-tuned version of dbmdz/german-gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.8196
- eval_runtime: 43.8543
- eval_samples_per_second: 86.993
- eval_steps_per_second: 5.45
- epoch: 9.0
- step: 11520 ## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 22 ### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # german-poetry-gpt2

This model is a fine-tuned version of dbmdz/german-gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.8196
- eval_runtime: 43.8543
- eval_samples_per_second: 86.993
- eval_steps_per_second: 5.45
- epoch: 9.0
- step: 11520 ## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 22 ### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# german-poetry-gpt2

This model is a fine-tuned version of dbmdz/german-gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.8196
- eval_runtime: 43.8543
- eval_samples_per_second: 86.993
- eval_steps_per_second: 5.45
- epoch: 9.0
- step: 11520## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 22### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1