Points to Remember

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Points to Remember

The GPT-1 was launched in June 2018, and it was trained with diverse levels of unlabeled textual corpus data to develop a strong natural language understanding base with fine-tuning and generative pre-training.

The study showed how pre-training improved the model’s zero shot performance on a variety of NLP tasks, including sentiment analysis, question answering, and schema resolution.

GPT-1 performed better than specifically trained supervised state-of-the-art models in 9 out of 12 tasks the models were compared on.

The GPT -1 model once again performed significantly better on these tasks than the prior best results, with gains of up to 8.9% on Story Cloze and 5.7% overall on RACE.

The next version of the GPT model was introduced in 2019, GPT-2 which was trained on a larger dataset and enriched with more parameters to make this model better.

The foundation for zero-shot task transfer, mentioned in GPT-2, is task conditioning.

GPT 2’s capacity to transfer zero shot tasks is intriguing.

As a special case of zero shot task transfer, zero shot learning occurs when no examples are given at all, and the model is instructed to perform the task.

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