--- library_name: transformers license: mit base_model: FacebookAI/xlm-roberta-large tags: - generated_from_trainer metrics: - accuracy model-index: - name: populism_classifier_bsample_122 results: [] --- # populism_classifier_bsample_122 This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9244 - Accuracy: 0.0686 - 1-f1: 0.1121 - 1-recall: 1.0 - 1-precision: 0.0594 - Balanced Acc: 0.5052 ## 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: 3e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 15 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.8259 | 1.0 | 11 | 0.8656 | 0.0637 | 0.1116 | 1.0 | 0.0591 | 0.5026 | | 0.7058 | 2.0 | 22 | 0.8846 | 0.0760 | 0.1129 | 1.0 | 0.0599 | 0.5091 | | 0.7391 | 3.0 | 33 | 0.9244 | 0.0686 | 0.1121 | 1.0 | 0.0594 | 0.5052 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3