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datasets:
  - niltheory/ExistenceTypes
language:
  - en

Iteration #1: base distilBert used to train the model with a data training of 96.

Iteration #2: Increased the data training from 96 to 296. Which greatly increased the accuracy scores, albeit there is some edge cases.

Iteration #3:

Switched from bert-base-uncased to bert-large-cased-whole-word-masking. Which it has more contextual sensitivity and is slightly more accurate than Iteration #2. It's overall more nuanced and sensitive.