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>_this is the "latest" version of the model that has been trained the longest, currently at 70k steps_
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- motivation: typical datasets for summarization models are in the vein of PubMed / arXiv; for my use cases, I have found summaries created by models pretrained on these to be
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- summarizing text via arXiv models will typically make the summary sound so needlessly complicated that you might as well have read the original text in that time.
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- this model is one attempt to help with that by using the [booksum](https://arxiv.org/abs/2105.08209) dataset to provide **explanatory summarization**
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- this model has been trained for seven epochs total (approx 70,000 steps) and is closer to finished.
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## Alternate Checkpoint
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- if experiencing runtime
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---
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>_this is the "latest" version of the model that has been trained the longest, currently at 70k steps_
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- motivation: typical datasets for summarization models are in the vein of PubMed / arXiv; for my use cases, I have found summaries created by models pretrained on these to be mostly useless.
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- summarizing text via arXiv models will typically make the summary sound so needlessly complicated that you might as well have read the original text in that time.
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- this model is one attempt to help with that by using the [booksum](https://arxiv.org/abs/2105.08209) dataset to provide **explanatory summarization**
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- this model has been trained for seven epochs total (approx 70,000 steps) and is closer to finished.
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## Alternate Checkpoint
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- if experiencing runtime/memory issues, try [this earlier checkpoint](https://huggingface.co/pszemraj/bigbird-pegasus-large-booksum-40k-K) at 40,000 steps which is almost as good at the explanatory summarization task but runs faster.
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