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- Two-stage training script (adapt_model.py) with JSON config - Evaluation script (evaluate_embedding_model.py) for CLSD, STS, bitext mining - Sample training notebook and config - Noisy finetuning data (sampled/concat variants, LREC historical articles) - Clean and noisy CLSD evaluation datasets - STS-17 cross-lingual evaluation datasets - Multi-script random character noise generator - Large files (bitext JSONL, full TED/X-News CSVs) excluded - see READMEs for download links
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… rename noise script folder - Migrate sample_training.ipynb and adapt_model.py to SentenceTransformerTrainer - Replace deprecated InputExample/DataLoader/model.fit with HFDataset/Trainer - Use bf16 only on Ampere+ GPUs (fixes CUDA assert on T4) - Replace warmup_ratio with warmup_steps (Transformers v5+ deprecation) - Rename generate_random_character_noise_latin_alphabet -> generate_random_character_noise - Remove torch CPU pins from requirements.txt (Colab compatibility) - Add accelerate>=0.26.0 to requirements.txt
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This PR adds the resources and code for the LREC OCR-robust multilingual embeddings recipe.
What's included
Datasets
ACL/subdirectoryCode