
# murakami_rugpt3small

## Model description

Fine-tuned from [sberbank-ai/rugpt3small_based_on_gpt2](https://huggingface.co/sberbank-ai/rugpt3small_based_on_gpt2)

## Intended uses & limitations

Generate novels in the style of Haruki Murakami, in Russian. 

Just my exercise to learn the Huggingface ecosystem, really.

## Training and evaluation data

Fine-tuned on [murakami](https://huggingface.co/datasets/vldsavelyev/murakami) dataset, 
which was built from Russian translations of novels by Haruki Murakami.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- gradient_checkpointing: True
- num_epochs: 3.0
- mixed_precision_training: Native AMP (fp16=True)


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"language": ["ru"], "tags": ["generated_from_trainer"], "datasets": ["murakami"], "model-index": [{"name": "murakami_rugpt3small", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer ru dataset:murakami autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #ru #dataset-murakami #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# murakami_rugpt3small

## Model description

Fine-tuned from sberbank-ai/rugpt3small_based_on_gpt2

## Intended uses & limitations

Generate novels in the style of Haruki Murakami, in Russian. 

Just my exercise to learn the Huggingface ecosystem, really.

## Training and evaluation data

Fine-tuned on murakami dataset, 
which was built from Russian translations of novels by Haruki Murakami.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- gradient_checkpointing: True
- num_epochs: 3.0
- mixed_precision_training: Native AMP (fp16=True)


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

# murakami_rugpt3small ## Model description

Fine-tuned from sberbank-ai/rugpt3small_based_on_gpt2 ## Intended uses & limitations

Generate novels in the style of Haruki Murakami, in Russian. 

Just my exercise to learn the Huggingface ecosystem, really. ## Training and evaluation data

Fine-tuned on murakami dataset, 
which was built from Russian translations of novels by Haruki Murakami. ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- gradient_checkpointing: True
- num_epochs: 3.0
- mixed_precision_training: Native AMP (fp16=True) ### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #ru #dataset-murakami #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # murakami_rugpt3small ## Model description

Fine-tuned from sberbank-ai/rugpt3small_based_on_gpt2 ## Intended uses & limitations

Generate novels in the style of Haruki Murakami, in Russian. 

Just my exercise to learn the Huggingface ecosystem, really. ## Training and evaluation data

Fine-tuned on murakami dataset, 
which was built from Russian translations of novels by Haruki Murakami. ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- gradient_checkpointing: True
- num_epochs: 3.0
- mixed_precision_training: Native AMP (fp16=True) ### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #ru #dataset-murakami #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# murakami_rugpt3small## Model description

Fine-tuned from sberbank-ai/rugpt3small_based_on_gpt2## Intended uses & limitations

Generate novels in the style of Haruki Murakami, in Russian. 

Just my exercise to learn the Huggingface ecosystem, really.## Training and evaluation data

Fine-tuned on murakami dataset, 
which was built from Russian translations of novels by Haruki Murakami.### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- gradient_checkpointing: True
- num_epochs: 3.0
- mixed_precision_training: Native AMP (fp16=True)### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2