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@@ -4,7 +4,6 @@ base_model: gpt2
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  tags:
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  - generated_from_trainer
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  - code
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- - not-for-all-audiences
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  model-index:
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  - name: codeparrot-ds
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  results: []
@@ -23,21 +22,21 @@ should probably proofread and complete it, then remove this comment. -->
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  # GPT2-Codeparrot
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- This model is trained from scratch using random initilization [gpt2](https://huggingface.co/gpt2) on the validaition set of codeparrot.
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  ## Model description
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- More information needed
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-
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  ## Intended uses & limitations
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- More information needed
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-
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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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  - num_epochs: 1
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  - mixed_precision_training: Native AMP
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- ### Training results
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  ### Framework versions
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  - Transformers 4.42.4
 
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  tags:
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  - generated_from_trainer
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  - code
 
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  model-index:
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  - name: codeparrot-ds
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  results: []
 
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  # GPT2-Codeparrot
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+ Generative Pre-trained Transformer 2 (GPT-2) is a large language model from OpenAI that was first introduced in [gpt2](https://huggingface.co/gpt2). It is a decoder-only Transformer model trained using a masked language modeling (MLM) objective. This means the model is trained to predict the next word in a sequence, given the previous words. GPT-2 models are known for their ability to generate realistic and coherent text, making them useful for a variety of natural language processing tasks such as text generation, translation, and question answering.
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  ## Model description
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+ This model is a base GPT-2 architecture with [insert number] parameters. It was trained on the huggingface-course/codeparrot-ds-valid dataset, which is a small subset of the original WebText dataset used to train GPT-2. Due to the limited training data, this model may not perform as well as other pre-trained GPT-2 models available on Hugging Face.
 
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  ## Intended uses & limitations
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+ This model is intended for personal learning and exploration of the GPT-2 architecture. Due to its limited training data, it may not be suitable for real-world applications.
 
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  ## Training and evaluation data
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+ This model was trained using the Transformers library with the following specifications:
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+ - Training Data: `huggingface-course/codeparrot-ds-valid`
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+ - Training Script: [Training_a_causal_language_model_from_scratch](https://github.com/kailas711/HugginFace-NLP-Course/blob/af464abed3f79fe7434f3310ceb97bfb68cddcef/Training_a_causal_language_model_from_scratch.ipynb)
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+ -
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  ### Training hyperparameters
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  - num_epochs: 1
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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  - Transformers 4.42.4