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Model: overthelex/qwen2.5-14b-edrsr-legal-uk Source: Original Platform
2026-09-02 06:08:16 +08:00
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--- a/README.md
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+---
+license: apache-2.0
+language:
+- uk
+base_model: Qwen/Qwen2.5-14B
+tags:
+- legal
+- ukrainian
+- continued-pretraining
+- court-decisions
+datasets:
+- overthelex/edrsr-court-decisions
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Qwen2.5-14B-EDRSR-Legal-UK
+
+Ukrainian legal domain model obtained by continued pretraining (CPT) of [Qwen/Qwen2.5-14B](https://huggingface.co/Qwen/Qwen2.5-14B) on the EDRSR corpus of Ukrainian court decisions.
+
+Part of a scaling experiment (0.5B / 1.5B / 3B / 14B) for the PhD dissertation at Glushkov Institute of Cybernetics, NAS of Ukraine.
+
+## Training Data
+
+- **Corpus:** Unified State Register of Court Decisions of Ukraine (EDRSR)
+- **Documents:** 33.9M court decisions (after dedup + quality filtering from 38.5M)
+- **Tokens:** 161.4B tokens (Qwen2 BPE tokenizer, fertility = 0.515 for Ukrainian legal text)
+- **Sequence length:** 8,192 tokens
+- **Shards:** 1,233 pre-packaged numpy shards
+
+## Training Details
+
+- **Hardware:** 8x NVIDIA H100 SXM 80GB (NVIDIA Innovation Lab via Brev)
+- **Framework:** HuggingFace Trainer + DeepSpeed ZeRO-3
+- **Precision:** bfloat16
+- **Global batch size:** 128 sequences (1.05M tokens/step)
+- **Total steps:** 9,536 (10B tokens processed)
+- **Training time:** 44 hours
+- **Throughput:** 22K tokens/sec, 44.9 sec/step
+
+## Results
+
+| Metric | Value |
+|--------|-------|
+| Initial loss (step 10) | 0.84 |
+| Final loss (step 9,536) | 0.22 |
+| Loss reduction | -74% |
+| Base perplexity | 2.84 |
+| **CPT perplexity** | **1.28** |
+| **Perplexity reduction** | **-54.8%** |
+
+## Scaling Law
+
+All four models in the series converge to similar perplexity after CPT:
+
+| Model | Base PPL | CPT PPL | Reduction |
+|-------|----------|---------|-----------|
+| [0.5B](https://huggingface.co/overthelex/qwen2.5-0.5b-edrsr-legal-uk) | 6.83 | 1.35 | -80% |
+| [1.5B](https://huggingface.co/overthelex/qwen2.5-1.5b-edrsr-legal-uk) | 4.61 | 1.31 | -72% |
+| [3B](https://huggingface.co/overthelex/qwen2.5-3b-edrsr-legal-uk) | 3.83 | 1.30 | -66% |
+| [14B](https://huggingface.co/overthelex/qwen2.5-14b-edrsr-legal-uk) | 2.84 | 1.28 | -55% |
+
+## Intended Use
+
+This is a **base model** (not instruction-tuned). It is intended for:
+- Research on domain adaptation of LLMs for low-resource legal languages
+- Downstream fine-tuning for Ukrainian legal NLP tasks
+- Scaling law analysis of continued pretraining
+- Perplexity evaluation on Ukrainian legal text
+
+## Limitations
+
+- Not instruction-tuned; will not follow instructions or chat
+- Trained on Ukrainian court decisions only; may not generalize to other legal systems
+
+## Related Resources
+
+- [EDRSR Court Decisions Dataset](https://huggingface.co/datasets/overthelex/edrsr-court-decisions)
+- [Tokenizer Fertility Paper (arXiv:2605.14890)](https://arxiv.org/abs/2605.14890)
+- [Citation Graph Paper (arXiv:2605.15362)](https://arxiv.org/abs/2605.15362)
+- [Statute Retrieval Paper (arXiv:2605.17639)](https://arxiv.org/abs/2605.17639)
+- [UA-StatuteRetrieval Benchmark](https://huggingface.co/datasets/overthelex/ua-statute-retrieval)
--- a/config.json
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+}
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