glot500-base-plains-cree-en-clkd-direct

cis-lmu/glot500-base adapted for Plains Cree figurative language detection via Cross-Lingual Knowledge Distillation (CLKD) (no TLM warmup).

Method

Inspired by Cross-Lingual Knowledge Distillation (ACL 2023).

CLKD pipeline:

  1. Teacher: KonradBRG/deberta-v3-base-figurative (frozen, English)
  2. Student base: cis-lmu/glot500-base
  3. All layers trainable.

The teacher predicts soft label distributions on English translations of Plains Cree sentences. The student is trained to match these distributions on the Cree side via KL divergence.

Training data: ~9,000 Cree–English parallel sentence pairs Temperature: 2.0 | Epochs: 10 | Hardware: 1× NVIDIA A100 40 GB

Labels: literal (0), idiom (1), metaphor (2), simile (3)

Citation

If you use this model, please cite the associated thesis/paper (TBD).

Data

Training data includes:

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