--- tags: - generated_from_trainer datasets: - akahana/GlotCC-V1-jav-Latn metrics: - accuracy model-index: - name: roberta-javanese results: - task: name: Masked Language Modeling type: fill-mask dataset: name: akahana/GlotCC-V1-jav-Latn default type: akahana/GlotCC-V1-jav-Latn args: default metrics: - name: Accuracy type: accuracy value: 0.5302221081011683 --- # roberta-javanese This model is a fine-tuned version of [](https://huggingface.co/) on the akahana/GlotCC-V1-jav-Latn default dataset. It achieves the following results on the evaluation set: - Loss: 2.9194 - Accuracy: 0.5302 ## 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: 5e-05 - train_batch_size: 16 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 35.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1