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README.md
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# glot500-base-plains-cree-en-clkd-direct
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## Method
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Tests whether Glot500's broad multilingual representations are sufficient for cross-lingual figurative language transfer into Plains Cree without explicit alignment fine-tuning.
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**Temperature:** 2.0 | **Epochs:** 10 | **Hardware:** 1× NVIDIA A100 40 GB
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**Labels:** `literal` (0), `idiom` (1), `metaphor` (2), `simile` (3)
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If you use this model, please cite the associated thesis/paper (TBD).
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## Data
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Training data includes:
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- [Bloomfield (1934) *Plains Cree Texts*](https://bloomfield.kiyanaw.net) (scraped and sentence-aligned)
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- [EdTeKLA Indigenous Languages Corpora](https://github.com/EdTeKLA/IndigenousLanguages_Corpora)
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# glot500-base-plains-cree-en-clkd-direct
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cis-lmu/glot500-base adapted for Plains Cree figurative language detection via Cross-Lingual Knowledge Distillation (CLKD) (no TLM warmup).
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## Method
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Inspired by [Cross-Lingual Knowledge Distillation (ACL 2023)](https://aclanthology.org/2023.findings-acl.885/).
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**CLKD pipeline:**
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1. Teacher: `KonradBRG/deberta-v3-base-figurative` (frozen, English)
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2. Student base: `cis-lmu/glot500-base`
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3. All layers trainable.
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The teacher predicts soft label distributions on English translations of Plains Cree sentences.
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The student is trained to match these distributions on the Cree side via KL divergence.
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**Training data:** ~9,000 Cree–English parallel sentence pairs
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**Temperature:** 2.0 | **Epochs:** 10 | **Hardware:** 1× NVIDIA A100 40 GB
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**Labels:** `literal` (0), `idiom` (1), `metaphor` (2), `simile` (3)
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If you use this model, please cite the associated thesis/paper (TBD).
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## Data
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Training data includes:
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- [Bloomfield (1934) *Plains Cree Texts*](https://bloomfield.kiyanaw.net) (scraped and sentence-aligned)
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- [EdTeKLA Indigenous Languages Corpora](https://github.com/EdTeKLA/IndigenousLanguages_Corpora)
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