Hello, I would like a model that allows you to automatically generate questions according to the course you want. For example, “Arithmetic: In a geometric proposition the sum of the extremes is 10, the sum of the middle terms is 8. Find the absolute value of the difference of the 2nd. consequent with the 1st. antecedent.”
From the arithmetic question posed, I would also like to receive your answer process, so that in this way I can print it.
@Jorge_Barrera Welcome to Tensorflow Forum !
Here’s a conceptual outline for creating a TensorFlow model for automatic question generation and answering in arithmetic:
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Data Collection and Preparation: Gather a large dataset of arithmetic questions and their corresponding answers and solutions. Tokenize questions and answers into words or subwords. Create numerical representations using techniques like word embeddings.
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Model Architecture: Consider a sequence-to-sequence model with an encoder-decoder architecture. The encoder processes the input question and encodes its meaning into a latent representation. The decoder generates the output question or answer based on the encoded information. Explore different attention mechanisms to enhance the model’s ability to focus on relevant parts of the input.
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Training: Train the model on the prepared dataset using TensorFlow’s APIs for model building and training. Experiment with hyperparameters and optimizers to fine-tune performance. Monitor training progress using appropriate metrics like loss and accuracy.
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Question Generation: To generate a question, provide a prompt (e.g., “Arithmetic: Generate a question about fractions”). Use the model’s decoder to generate a question based on the prompt and its understanding of arithmetic concepts. Implement techniques to control the difficulty level of the generated questions.
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Answer Generation: To answer a question, provide the question as input to the model. The model will generate an answer along with its solution steps.
Let me know if this helps!