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Long-Range-Arena Evaluation #49

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ClashLuke opened this issue May 18, 2022 · 0 comments
Open

Long-Range-Arena Evaluation #49

ClashLuke opened this issue May 18, 2022 · 0 comments
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downstream Changes code wrapping the core model engineering Software-engineering problems that don't require ML-Expertise ML Requires machine-learning knowledge (can be built up on the fly)

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@ClashLuke
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Currently, we only know that our model is better than the baseline because of its lower loss at less training time. However, we could run some benchmarks such as LRA to see how well our long-context model performs in a real-world scenario. While LRA doesn't leverage our capabilities ideally (unlike, for example, #5 and #9), it'd still allow us to have preliminary evaluation results on a well-known benchmark dataset.
This issue tacks the progress of integrating our model into LRA, even though it should happen in a separate codebase.
@ClashLuke ClashLuke added engineering Software-engineering problems that don't require ML-Expertise ML Requires machine-learning knowledge (can be built up on the fly) downstream Changes code wrapping the core model labels May 18, 2022
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