cihanunlu/berturk-histr-lora-ner

Model Card for Model ID

Overview

Base model	cihanunlu/BerTurk_Ottoman_Full_DAPT
Adapter type	LoRA (Low-Rank Adaptation) built with HF PEFT
Task	Named-Entity Recognition  •  BIO tags PER / LOC / O
Language	Ottoman / Late-Ottoman Turkish (Latin transliteration)
Repo contents	≈ 2 MB LoRA weights (adapter_model.bin, adapter_config.json) + tokenizer files

Attach it to the BerTurk_Ottoman_Full_DAPT checkpoint to obtain a lightweight NER model fine-tuned on the HiSTR corpus.

• • Suitable for historical/Ottoman Turkish NER focusing on PERSON and LOCATION.
• • Performance drops on modern Turkish or domain-specific jargon.
• • Adapter inherits ethical constraints and biases of the base BerTurk model.

3 Evaluation

• Dev (HiSTR) — best checkpoint (epoch 4)

  • Precision – 77.3 %
  • Recall – 84.9 %
  • F1 – 80.9 %

• Test (Rûznâmçe)

  • Precision – 54.4 %
  • Recall – 52.8 %
  • F1 – 53.6 %

4 Training hyper-parameters

• LoRA rank r: 16
• LoRA α: 16
• Dropout: 0.10
• Peak learning rate: 5 × 10⁻⁴
• Effective batch size: 16
• Epochs: 5
• Mixed precision: FP16