--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-base tags: - generated_from_trainer metrics: - accuracy - f1 - recall - precision model-index: - name: populism_model97 results: [] --- # populism_model97 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: 0.4236 - Accuracy: 0.9109 - F1: 0.5263 - Recall: 0.5882 - Precision: 0.4762 ## 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: 128 - eval_batch_size: 128 - 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: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| | No log | 1.0 | 13 | 0.2727 | 0.8589 | 0.5366 | 0.9706 | 0.3708 | | No log | 2.0 | 26 | 0.2482 | 0.8936 | 0.6055 | 0.9706 | 0.44 | | No log | 3.0 | 39 | 0.3954 | 0.9134 | 0.5333 | 0.5882 | 0.4878 | | 0.267 | 4.0 | 52 | 0.6119 | 0.9158 | 0.4848 | 0.4706 | 0.5 | | 0.267 | 5.0 | 65 | 0.4236 | 0.9109 | 0.5263 | 0.5882 | 0.4762 | ### Framework versions - Transformers 4.48.0.dev0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0