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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: chef-gpt-base
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# chef-gpt-base
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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## Model description
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 16
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- eval_batch_size: 4
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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- mixed_precision_training: Native AMP
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---
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license: mit
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model-index:
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- name: chef-gpt-base
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results: []
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language:
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- bg
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pipeline_tag: text-generation
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# chef-gpt-base
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GPT-2 architecture trained to generate recipes based on ingredients.
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## Model description
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This is GPT-2 pretrained on a custom dataset of recipies in Bulgarian.
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You can find the dataset [here](https://www.kaggle.com/datasets/auhide/bulgarian-recipes-dataset).
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## Usage
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```python
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```
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## Additional tokens
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- [ING] - ingredients token; denotes the begining of the tokens representing the ingredients
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- [EOL] - end-of-line token; equivalent to a newline
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- [REC] - recipe token; denotes the begining of the recipe
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