Jev vs a 310M encoder I trained myself: 750 rows, three tasks, two different winners

Automated excerpt

The same architecture family, trained on my labels, scored 88. 8 / 92. 8 / 75. 2. Trained on 250 of my labels, the same generation of model scored 88. 8 / 92. 8 / 75. 2. At 250 labels the trained encoder is already at parity with Jev on the tasks Jev is strong at, and ahead where Jev is weak.

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