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GPT from scratch

This repo contains code to train a GPT from scratch. The dataset is taken from the RedPajama 1 trillion data. Only samples from this are taken and used for the training purposes. The implementation of the transformer is similar to the LitGPT.

The trained model has a parameter count of about 160M. The final training loss was found to be 3.2154.

The Hugging Face implementation can be found here.

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The training details can be found in the attached notebooks. The initial training was stopped when the loss was around 4.

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Using the checkpoint, the second part of the training was resumed and stopped when it went below 3.5.

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Sample Predictions

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