Phazel/

persian-sentiment-analysis-snappfood-bow

Persian sentiment analysis (polarity) for short user-generated text, trained on the SnappFood review corpus. A hashed-bigram linear textcat with no vectors and no transformer: 85.92 macro F on the held-out test split at 7,868 docs/second on an i5-7200U (2 cores). Fine-tuned ParsBERT scores 87.31 on the same split at 229 docs/second on a Tesla T4, so this model gives up 1.4 F for a 34x throughput gain and no GPU requirement. Labels: HAPPY, SAD.

Trained from configs/textcat_bow.cfg. No vectors are bundled, so the wheel is ~2 MB and inference is pure CPU. Tokenisation is spaCy's blank Persian tokenizer with no normalisation, which is deliberate: hashed bigrams absorb ZWNJ and elongation variants as distinct features rather than collapsing them.