Agriculture Query Routing Model (MuRIL, Hindi/Punjabi)
MuRIL fine-tuned for native Hindi/Punjabi farmer-query intent classification (pest_id/irrigation/mandi_price/scheme_eligibility/ other). AutoScientist Challenge Part 2, Agriculture category.
Results
Accuracy 92.5%, Macro-F1 0.240 (held-out 20% split, 40 rows).
Known limitation, disclosed honestly — the most extreme in this
round's five submissions: built without ULCA registration (multi-day
external dependency) to fit the deadline, using IndicCorpV2 general
web text instead of genuine farmer queries. The high accuracy is
almost entirely the other class's dominance (182/200 training rows),
not genuine skill distinguishing pest_id/irrigation/mandi_price/
scheme_eligibility (2-6 examples each). The pipeline is validated and
ready for real ULCA farmer-query data; see the source project's
PART2_SUBMISSION.md for the full writeup.
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Model tree for tojpaj/agriculture-routing-model
Base model
google/muril-base-cased