--- library_name: transformers license: mit base_model: FacebookAI/xlm-roberta-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: kat-Geor results: [] language: - ka --- # kat-Geor This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8029 - Accuracy: 0.8658 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - total_train_batch_size: 32 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 100000 ### Citation Information If you use this model in your work, please cite the following paper. Additionally, if you require more details on training and performance, refer to the paper: ```bibtex @misc{gurgurov2025smallmodelsbigimpact, title={Small Models, Big Impact: Efficient Corpus and Graph-Based Adaptation of Small Multilingual Language Models for Low-Resource Languages}, author={Daniil Gurgurov and Ivan Vykopal and Josef van Genabith and Simon Ostermann}, year={2025}, eprint={2502.10140}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2502.10140}, } ```