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  - **Model Type**: GPTNeoXForCausalLM
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  - **Model Training Details**: The model is trained using [crumb/flan-ul2-tinystories](https://huggingface.co/datasets/crumb/flan-ul2-tinystories) which contains around a quarter of a million examples generated from Flan-UL2 (20b) with the prompt "Write a short story using the vocabulary of a first-grader."
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- ![](https://cdn.discordapp.com/attachments/1074346695191711875/1126796435577393213/image.png)
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  ## Model Description
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  This model is trained with the specific purpose of generating short narratives using a vocabulary limited to the level of a first-grader. In terms of complexity and language usage, the model is designed to produce simplistic and easily comprehensible text.
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  ## Validation and Performance
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- The model's performance was evaluated using a held-out validation set, which constitutes 1% of the original dataset. During evaluation, the model achieved a loss of 2.284920. During training, the model achieved a loss of 2.647377
 
 
 
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  - **Model Type**: GPTNeoXForCausalLM
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  - **Model Training Details**: The model is trained using [crumb/flan-ul2-tinystories](https://huggingface.co/datasets/crumb/flan-ul2-tinystories) which contains around a quarter of a million examples generated from Flan-UL2 (20b) with the prompt "Write a short story using the vocabulary of a first-grader."
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  ## Model Description
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  This model is trained with the specific purpose of generating short narratives using a vocabulary limited to the level of a first-grader. In terms of complexity and language usage, the model is designed to produce simplistic and easily comprehensible text.
 
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  ## Validation and Performance
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+ The model's performance was evaluated using a held-out validation set, which constitutes 1% of the original dataset. During evaluation, the model achieved a loss of 2.284920. During training, the model achieved a loss of 2.647377
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+ ![](https://cdn.discordapp.com/attachments/1074346695191711875/1126796435577393213/image.png)