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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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datasets: |
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- NeuralNovel/Neural-Story-v1 |
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library_name: transformers |
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inference: false |
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--- |
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# NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story |
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The **Mistral-7B-Instruct-v0.2-Neural-Story** model, developed by NeuralNovel and funded by Techmind, is a language model finetuned from Mistral-7B-Instruct-v0.2. |
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Designed to generate instructive and narrative text, with a specific focus on storytelling. |
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This fine-tune has been tailored to provide detailed and creative responses in the context of narrative and optimised for short story telling. |
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Based on mistralAI, with apache-2.0 license, suitable for commercial or non-commercial use. |
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### Data-set |
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The model was finetuned using the Neural-Story-v1 dataset. |
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### Benchmark |
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| Metric | Value | |
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|-----------------------|---------------------------| |
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| Avg. | **64.96** | |
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| ARC | 64.08 | |
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| HellaSwag | **66.89** | |
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| MMLU | 60.67 | |
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| TruthfulQA | 66.89 | |
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| Winogrande | **75.85** | |
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| GSM8K | 38.29 | |
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Evaluated on **HuggingFaceH4/open_llm_leaderboard** |
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### Summary |
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Fine-tuned with the intention of generating creative and narrative text, making it more suitable for creative writing prompts and storytelling. |
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#### Out-of-Scope Use |
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The model may not perform well in scenarios unrelated to instructive and narrative text generation. Misuse or applications outside its designed scope may result in suboptimal outcomes. |
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### Bias, Risks, and Limitations |
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The model may exhibit biases or limitations inherent in the training data. It is essential to consider these factors when deploying the model to avoid unintended consequences. |
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While the Neural-Story-v0.1 dataset serves as an excellent starting point for testing language models, users are advised to exercise caution, as there might be some inherent genre or writing bias. |
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### Hardware and Training |
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``` |
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n_epochs = 3, |
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n_checkpoints = 3, |
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batch_size = 12, |
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learning_rate = 1e-5, |
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``` |
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*Sincere appreciation to Techmind for their generous sponsorship.* |
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