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rmtariq/ft-Malay-bert
ft-Malay-bert is a text classification model from rmtariq. Use it when you need a label for a piece of text. The card lists the license as apache-2.0.
Fine-tuned sentiment classifier (3-class) for Malaysian higher-education feedback. Trained on MYUniDialectSentiment840 (840 samples, 14 dialects, 20 topics, 15 learning contexts), a hand-curated balanced corpus coveri…
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.safetensors711 MB · 99%
From the Hugging Face model README
Fine-tuned sentiment classifier (3-class) for Malaysian higher-education feedback. Trained on MYUniDialectSentiment840 (840 samples, 14 dialects, 20 topics, 15 learning contexts), a hand-curated balanced corpus covering Standard Malay, 13 regional dialects, and Manglish code-switching.
negativeneutralpositive| split | accuracy | f1_macro |
|---|---|---|
| validation (n=105) | 1.0000 | 1.0000 |
| test (n=147) | 0.9932 | 0.9932 |
Sentiment / emotion monitoring of student feedback for Malaysian higher-education institutions. Designed to handle code-switched, dialect-heavy and informal academic discourse.
rmtariq/ft-Malay-bertMYUniDialectSentiment840 — 840 samples, balanced on sentiment, stratified
70/12.5/17.5 train/val/test by sentiment-x-dialect.