xlmr-slot-v2

Ferman slot tagger (XLM-R base, v2)

Tags the slots (date, time, event name, list name, person, place and others) inside assistant commands in English, Arabic, Sorani and Badini, using BIO labels. Fine-tuned from xlm-roberta-base. Pairs with OmarSY11/xlmr-intent-v2. Part of the Ferman project: https://github.com/omarGH99/ferman-ai-assistant

Usage

from transformers import pipeline
tag = pipeline("token-classification", model="OmarSY11/xlmr-slot-v2", aggregation_strategy="simple")
print(tag("remind me to call mum tomorrow at 7pm"))

Training data

Rows of the v2 configuration of OmarSY11/ferman-nlu that carry slot annotations (annot column), train split. English and Arabic derive from MASSIVE; Sorani and Badini are machine-translated.

Arabic caveat: only 304 Arabic rows carry slot annotations in this release (MASSIVE has more; they were not carried over), so Arabic slot extraction is barely trained and was not measured.

Training

The notebook is in the repo: ml/train_xlmr_slot_v2_runpod.ipynb.

Results

Entity-level (seqeval) on the held-out test split of the v2 data.

Kurdish test sets are small, so those figures carry wide uncertainty.

Limitations

• Arabic slots are unmeasured and trained on very little data.
• Kurdish data is machine-translated and informally reviewed by one person (native Badini, non-native Sorani).
• Slots come from a fixed MASSIVE-style label set; unseen slot types are not handled.

License and citation

Model weights: MIT, like the base model. Training data: CC BY 4.0, derived from MASSIVE (FitzGerald et al., 2022, arXiv:2204.08582), which must be credited. Please also cite https://github.com/omarGH99/ferman-ai-assistant.