--- license: apache-2.0 base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ tags: - generated_from_trainer model-index: - name: mistral-pdf-to-quizz-7b results: [] --- # mistral-pdf-to-quizz-7b This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ). ## Model description - Trained on 168 prompts that generate in order to generate a multiple question choices responses (https://huggingface.co/datasets/fbellame/pdf_to_quizz_mistral) ``` [INST] You are a teacher preparing questions for a quiz. Given the following document, please generate 1 multiple-choice questions (MCQs) with 4 options and a corresponding answer letter based on the document.\\n\\nExample question:\\n\\nQuestion: question here\\nCHOICE_A: choice here\\nCHOICE_B: choice here\\nCHOICE_C: choice here\\nCHOICE_D: choice here\\nAnswer: A or B or C or D\\n\\nThese questions should be detailed and solely based on the information provided in the document.\\n here are the inputs \\n{doc}\\n[/INST] doc=In 1229, the King had to struggle with a long lasting strike at the University of Paris. The Quartier Latin was strongly hit by these strikes. question: What was the cause of the strike at the University of Paris in 1229? choice_A: The King's interference in university affairs choice_B: A shortage of resources for the university choice_C: A disagreement between faculty members choice_D: The Quartier Latin being strongly hit by a natural disaster reponse: choice_B ``` ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 600 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.35.0.dev0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1