--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-base-multilingual-cased tags: - generated_from_trainer metrics: - accuracy model-index: - name: populism_classifier_021 results: [] --- # populism_classifier_021 This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5186 - Accuracy: 0.9229 - 1-f1: 0.6 - 1-recall: 0.6562 - 1-precision: 0.5526 - Balanced Acc: 0.8024 ## 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 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.3938 | 1.0 | 12 | 0.3025 | 0.8733 | 0.5106 | 0.75 | 0.3871 | 0.8176 | | 0.2118 | 2.0 | 24 | 0.2972 | 0.8843 | 0.5435 | 0.7812 | 0.4167 | 0.8378 | | 0.1085 | 3.0 | 36 | 0.3442 | 0.8981 | 0.5432 | 0.6875 | 0.4490 | 0.8030 | | 0.1067 | 4.0 | 48 | 0.5186 | 0.9229 | 0.6 | 0.6562 | 0.5526 | 0.8024 | ### Framework versions - Transformers 4.56.0.dev0 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4