The author publishes the Palmyra-Med and Palmyra-Fin models, which outperform other comparable models, such as GPT-4, Med-PaLM-2 and Claude 3.5 Sonnet

The field of generative ai is increasingly focused on creating models tailored to specific industries, improving performance in areas such as healthcare and finance. This specialization aims to meet the specific demands of these sectors, which require high precision and regulatory compliance due to their complex and regulated nature.

In healthcare and finance, traditional ai models often fail to deliver the accuracy and efficiency needed for industry-specific tasks. Medical and financial applications demand models that can handle specialized data accurately and cost-effectively. Existing general-purpose models may need to fully address the complexities of these fields, leading to performance gaps and higher costs for industrial applications.

Medical and financial ai models such as GPT-4 and Med-PaLM-2 are widely used today. While these powerful models often require more specialized capabilities for advanced medical diagnostics and detailed financial analysis, this limitation highlights the need for more refined and focused models to deliver superior performance in these sectors.

To address these needs, the Writer team has developed two new domain-specific models: Palmyra-Med and Palmyra-Fin. Palmyra-Med is designed for medical applications, while Palmyra-Fin targets financial tasks. These models are part of Writer’s suite of language models and are designed to deliver exceptional performance in their respective domains. Palmyra-Med-70B distinguishes itself with its high accuracy on medical benchmarks, achieving an average score of 85.9%. This outperforms competitors such as Med-PaLM-2 and performs particularly well on clinical knowledge, genetics, and biomedical research. Its cost-effectiveness is truly laudable, with a price of $10 per million output tokens, substantially lower than the $60 charged by models such as GPT-4.

Designed for financial applications, Palmyra-Fin-70B has demonstrated exceptional results. It passed the CFA Level III exam with a score of 73%, outperforming general-purpose models such as GPT-4, which scored only 33%. Furthermore, in the long-fin-eval benchmark, Palmyra-Fin-70B outperformed other models including Claude 3.5 Sonnet and Mixtral-8x7b. This model excels in financial trend analysis, investment evaluations, and risk assessments, and shows its ability to handle complex financial data accurately.

Palmyra-Med-70B uses advanced techniques to achieve its high benchmark scores. It integrates a specialized dataset and tuning methodologies, including Direct Preference Optimization (DPO), to improve its performance on medical tasks. The model’s accuracy on multiple benchmarks, such as 90.9% on MMLU Clinical Knowledge and 83.7% on MMLU Anatomy, demonstrates its deep understanding of clinical procedures and human anatomy. It scores 94.0% and 80% on Genetics and Biomedical Research, respectively, underscoring its ability to interpret complex medical data and aid in research.

The Palmyra-Fin-70B approach involves extensive training on financial data and custom tuning. The model’s performance on the CFA Level III exam and its results on the long-fin-eval benchmark highlight its strong understanding of economic concepts and its ability to process and analyze large amounts of financial information effectively. The model’s 100% accuracy on information-seeking tasks reflects its ability to retrieve accurate information from lengthy financial documents.

In conclusion, Palmyra-Med and Palmyra-Fin represent significant advancements in specialized ai models for the medical and financial industries. Developed by Writer, these models offer increased accuracy and efficiency, addressing the specific needs of these sectors with a focus on cost-effectiveness and superior performance. They set a new standard for domain-specific ai applications, providing valuable tools for healthcare and financial professionals.

Review the Details, Model Palmyra-Fin-70B-32Kand Model Palmyra-Med-70b-32kAll credit for this research goes to the researchers of this project. Also, don't forget to follow us on twitter.com/Marktechpost”>twitter and join our Telegram Channel and LinkedIn GrAbove!. If you like our work, you will love our Newsletter..

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Nikhil is a Consultant Intern at Marktechpost. He is pursuing an integrated dual degree in Materials from Indian Institute of technology, Kharagpur. Nikhil is an ai and Machine Learning enthusiast who is always researching applications in fields like Biomaterials and Biomedical Science. With a strong background in Materials Science, he is exploring new advancements and creating opportunities to contribute.

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