--- license: mit tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: train results: [] --- # train This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0145 - Accuracy: 0.9966 - F1: 0.9966 ## 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: 2e-05 - train_batch_size: 64 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.2363 | 1.0 | 1422 | 0.0150 | 0.9963 | 0.9963 | | 0.0116 | 2.0 | 2844 | 0.0145 | 0.9966 | 0.9966 | ### Framework versions - Transformers 4.28.1 - Pytorch 1.11.0 - Datasets 2.12.0 - Tokenizers 0.13.3