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README.md
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## Summary
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This model presents a method for fine-tuning `distilbert/distilbert-base-uncased` on a dataset of approximately 8,000 synthetic and randomized document samples.
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Randomization has been introduced with token shuffling.
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## Dataset
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## Summary
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This model presents a method for fine-tuning `distilbert/distilbert-base-uncased` on a dataset of approximately 8,000 synthetic and randomized document samples.
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Randomization has been introduced with token shuffling and python `Faker` library.
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## Dataset
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