--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-base-multilingual-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: populism_classifier_048 results: [] --- # populism_classifier_048 This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5430 - Accuracy: 0.9712 - 1-f1: 0.56 - 1-recall: 0.4375 - 1-precision: 0.7778 - Balanced Acc: 0.7160 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.2627 | 1.0 | 24 | 0.2215 | 0.9791 | 0.7143 | 0.625 | 0.8333 | 0.8098 | | 0.3545 | 2.0 | 48 | 0.4833 | 0.9764 | 0.6667 | 0.5625 | 0.8182 | 0.7785 | | 0.0512 | 3.0 | 72 | 0.5430 | 0.9712 | 0.56 | 0.4375 | 0.7778 | 0.7160 | ### Framework versions - Transformers 4.56.0.dev0 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4