| # Model Card for Fine-Tuned MIXTRAL-based Ad Generation Model | |
| ## Model Description | |
| This model is a fine-tuned version of the MIXTRAL-7b model, specifically adapted for generating marketing emails. The fine-tuning process was aimed at enhancing the model's ability to generate cohesive and contextually relevant advertisements based on a given product and its description. This fine-tuning was achieved using the MarketMail-AI dataset. | |
| ## Fine-tuning Details | |
| ### Base Model | |
| - MIXTRAL-7b | |
| ### Dataset | |
| - MarketMail-AI | |
| ### Fine-tuning Objective | |
| - The model was fine-tuned to specialize in generating marketing emails. This was done by providing the model with numerous examples from the MarketMail-AI dataset, allowing it to adjust its weights accordingly and improve its generation capabilities in the context of marketing. | |
| ### Libraries Used | |
| - The fine-tuning process utilized `peft`, `transformers`, and `bitsandbytes` for an efficient and effective training experience. | |
| ### Training Approach | |
| - The model was not subjected to merely zero-shot, one-shot, or few-shot learning. Instead, it underwent a more extensive retraining process where it was exposed to numerous examples to better understand and generate marketing-related content. | |
| ## Intended Use | |
| ### Primary Use | |
| - The model is intended to assist in generating marketing emails. Users can input a product name and its description, and the model will generate a corresponding marketing email. | |
| ### Suitable for | |
| - This model is suitable for marketers, copywriters, and businesses looking to automate or enhance their email marketing campaigns. | |
| ## Limitations | |
| - While the model is fine-tuned for marketing email generation, its outputs should be reviewed and possibly edited for coherence, brand alignment, and effectiveness. | |
| - The model's performance is directly influenced by the quality and diversity of the data it was trained on. Biases in the MarketMail-AI dataset may be reflected in the generated content. | |
| ## Ethical Considerations | |
| ### Data Privacy | |
| - Ensure that any input data does not infringe on individual privacy or contain sensitive information. | |
| ### Content Generation | |
| - Users should be aware of the potential for the model to generate biased or inappropriate content and take steps to mitigate such issues. | |
| ## Conclusion | |
| This fine-tuned MIXTRAL-7b model represents a targeted effort to leverage advanced language model capabilities for marketing purposes. By focusing the training on a specific dataset and task, the model aims to provide more relevant and context-aware outputs, enhancing the efficiency and creativity of marketing email generation. | |