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  # chatgpt-gpt4-prompts-bart-large-cnn-samsum
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- This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on an [this](https://huggingface.co/datasets/fka/awesome-chatgpt-prompts) dataset.
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  It achieves the following results on the evaluation set:
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  - Train Loss: 1.2214
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  - Validation Loss: 2.7584
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  This model supports a [Streamlit](https://streamlit.io/) Web UI to run the chatgpt-gpt4-prompts-bart-large-cnn-samsum model:
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  [![Open In HF Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/Kaludi/ChatGPT-BingChat-GPT3-Prompt-Generator_App)
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- ## Model description
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- More information needed
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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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  # chatgpt-gpt4-prompts-bart-large-cnn-samsum
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+ This model generates ChatGPT/BingChat & GPT-3 prompts and is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on an [this](https://huggingface.co/datasets/fka/awesome-chatgpt-prompts) dataset.
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  It achieves the following results on the evaluation set:
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  - Train Loss: 1.2214
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  - Validation Loss: 2.7584
 
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  This model supports a [Streamlit](https://streamlit.io/) Web UI to run the chatgpt-gpt4-prompts-bart-large-cnn-samsum model:
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  [![Open In HF Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/Kaludi/ChatGPT-BingChat-GPT3-Prompt-Generator_App)
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  ### Training hyperparameters
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  The following hyperparameters were used during training: