Update README.md

README.md

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 - AbstractPhil/geolip-bertenstein
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+# GEOLIP CaptionBERT-8192-fingerprinted
+
+The next iteration will require an expanded fingerprinted specifically to the alignment of the data and the teachers at training time.
+
+The differentiation between what is learned and what is retained specifically expert-to-expert will enable this fingerprint to preserve the student model's integrity,
+which should allow cross_entropy training without complete geometric collapse and rapid overffiting.
+
+As it stands this model is too rigid to train heads on, but I will directly improve it today and instill a core memory of geometry.
+
+This geometry will be ever-learning, meaning when the core model trains from any experts, the bank must train as well. This geometry houses the entire
+internalized geometric embedding anchored fingerprinting spectrum, and this will likely evolve over the coming hours until the functional prototype comes
+to full fruition. Wish me luck as I design the reusable compact mechanism.
+
+
 # GEOLIP CaptionBERT-8192
 
 A 26M-parameter caption encoder whose embedding space is the geometric intersection of five independently trained language models. Trained from scratch via consensus distillation — no pretrained weights, no expert models at inference.