--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: populism_classifier_059 results: [] --- # populism_classifier_059 This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8546 - Accuracy: 0.9588 - 1-f1: 0.4286 - 1-recall: 0.375 - 1-precision: 0.5 - Balanced Acc: 0.6794 ## 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: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.8434 | 1.0 | 25 | 0.4296 | 0.8918 | 0.3636 | 0.75 | 0.24 | 0.8239 | | 0.0919 | 2.0 | 50 | 0.4744 | 0.9562 | 0.5143 | 0.5625 | 0.4737 | 0.7678 | | 0.0545 | 3.0 | 75 | 0.8546 | 0.9588 | 0.4286 | 0.375 | 0.5 | 0.6794 | ### Framework versions - Transformers 4.56.0.dev0 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4