This model is a full fine-tuned version of meta-math/MetaMath-Mistral-7B on the following datasets: — 🧮 TIGER-Lab/MathInstruct — 📐 microsoft/orca-math-word-problems-200k This model is finetuned using 8xRTX3090 + 1xRTXA6000 using axolotl. This prompt template is available as a chat template, which means you can format messages using the tokenizer.applychattemplate() method: — https://huggingface.co/bartowski/EulerMath-Mistral-7B-GGUF — https://huggingface.co/bartowski/EulerMath-Mistral-7B-exl2 Evaluation Results of this model are low due to the strict requirements for the eval GSM8K eval harness. I evaluated this model using tinyGSM8k which is a streamlined subset of 100 data points from the GSM8K dataset, enabling efficient evaluation of large language models with reduced computational resources. As you can see from the results, this model does not meet the required format for strict-match results but the given answers is actually correct. However, as indicated by the flexible-extract part, this model is actually quite proficient at math. Thanks to all the dataset authors mentioned in the datasets section. Thanks to axolotl for making the repository I used to make this model.
Модальности:
Генерация текста
Области применения:
Математика Следование инструкциям Диалог / чат
Задача: Генерация текста
Автор: Weyaxi
Теги: mistral, math, alpaca, synthetic data, instruct, axolotl, finetune, gpt4
Лайков: 3 | Загрузок: 25
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
