Model details

• Developed by: Paula Guerrero and Iker Gutierrez
• Affiliation: University of the Basque Country (EHU)
• Model type: LoRA adapter for HiTZ/Latxa-Qwen3-VL-8B-Instruct
• Languages: Catalan (ca), Basque (eu)
• Domain: Literary translation
• Base model: HiTZ/Latxa-Qwen3-VL-8B-Instruct
• Continued from: pguerrero-igutierrez/Latxa-Qwen3-8B-General-eu-ca
• Repository: pguerrero-igutierrez/Latxa-Qwen3-8B-Literary-v2-ca-eu
• Collection: pguerrero-igutierrez/mt-domain-adaptation-ca-eu

Sources

• Hugging Face repository: https://huggingface.co/pguerrero-igutierrez/Latxa-Qwen3-8B-Literary-v2-ca-eu
• Hugging Face collection: https://huggingface.co/collections/pguerrero-igutierrez/mt-domain-adaptation-ca-eu
• Project repository: https://github.com/pguerrero-igutierrez/MT-domain-adaptation
• Paper source: https://github.com/pguerrero-igutierrez/MT-domain-adaptation/tree/main/paper

Intended use

This model is intended for research on low-resource Catalan-Basque literary translation, especially in settings where in-domain parallel data is scarce and synthetic back-translation data is used for adaptation.

Supported prompting directions:

• eu->ca: Itzuli testu hau euskaratik katalanera:\n\n{source}
• ca->eu: Tradueix aquest text del català al basc:\n\n{source}

Out-of-scope use

• High-stakes use without human review
• Professional literary publishing without post-editing
• Medical, legal, or safety-critical translation workflows
• General multilingual tasks outside Catalan-Basque translation

Training data

This adapter was trained on the same literary corpora as literaryv1, built through Spanish-pivot synthetic data generation and back-translation:

• backtranslated-corpus/ca-literary_trilingual.json
• backtranslated-corpus/eu-literary-EhuHac.jsonl

The model was then continued from the project general checkpoint rather than trained directly from the base model.

Training procedure

• LoRA rank: 16
• LoRA alpha: 32
• LoRA dropout: 0.05
• Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
• Quantization: 4-bit NF4
• Max sequence length: 768
• Epochs: 3
• Batch size: 4
• Gradient accumulation: 8
• Learning rate: 5e-5
• Scheduler: cosine
• Warmup ratio: 0.05
• Seed: 42
• Checkpoint selection: best validation BLEU

Evaluation

Results on the literary held-out test set:

In the project experiments, this continued-adaptation literary model performed slightly below the direct literary SFT model (literaryv1) across the reported literary metrics.

Limitations

• Trained on synthetic literary supervision rather than human-translated in-domain CA-EU parallel data
• Literary quality aspects such as style, voice, and fluency are only partially captured by automatic metrics
• CA->EU literary performance remains challenging, especially under word-level metrics such as BLEU

Usage

This repository contains adapter weights, so it must be loaded on top of the base model.

python
Copy code
import torch
from peft import PeftModel
from transformers import AutoTokenizer, Qwen3VLForConditionalGeneration

base_id = "HiTZ/Latxa-Qwen3-VL-8B-Instruct"
adapter_id = "pguerrero-igutierrez/Latxa-Qwen3-8B-Literary-v2-ca-eu"

tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
base_model = Qwen3VLForConditionalGeneration.from_pretrained(
    base_id,
    device_map="auto",
    torch_dtype=torch.bfloat16 if torch.cuda.is_available() else torch.float32,
    trust_remote_code=True,
)
model = PeftModel.from_pretrained(base_model, adapter_id)

prompt = "Tradueix aquest text del català al basc:\n\nBon vespre."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Citation

If you use this model, please cite the project repository:

bibtex
Copy code
@misc{guerrero-gutierrez-2026-caeu-mt,
  title        = {Domain Adaptation for Catalan-Basque Machine Translation via Synthetic Data and Continued Fine-Tuning},
  author       = {Guerrero, Paula and Gutierrez, Iker},
  year         = {2026},
  note         = {Unpublished manuscript}
}

Contact

• Paula Guerrero: pguerrero005@ikasle.ehu.eus
• Iker Gutierrez: igutierrez134@ikasle.ehu.eus