--- license: mit base_model: xlm-roberta-large tags: - generated_from_trainer metrics: - accuracy model-index: - name: XLM_RoBERTa-Offensive-Language-Detection-8-langs-new results: [] --- # XLM_RoBERTa-Offensive-Language-Detection-8-langs-new This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8276 - Micro F1: 0.8721 - Macro F1: 0.8604 - Accuracy: 0.8721 ## 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: 1e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results ### Framework versions - Transformers 4.36.1 - Pytorch 2.1.0+cu121 - Datasets 2.13.1 - Tokenizers 0.15.0