--- 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_003 results: [] --- # populism_classifier_003 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: 0.2029 - Accuracy: 0.9704 - 1-f1: 0.8214 - 1-recall: 0.92 - 1-precision: 0.7419 - Balanced Acc: 0.9472 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.2206 | 1.0 | 11 | 0.1905 | 0.9645 | 0.7857 | 0.88 | 0.7097 | 0.9256 | | 0.2774 | 2.0 | 22 | 0.1687 | 0.9675 | 0.8070 | 0.92 | 0.7188 | 0.9456 | | 0.0912 | 3.0 | 33 | 0.1892 | 0.9675 | 0.8 | 0.88 | 0.7333 | 0.9272 | | 0.0528 | 4.0 | 44 | 0.2029 | 0.9704 | 0.8214 | 0.92 | 0.7419 | 0.9472 | ### Framework versions - Transformers 4.56.0.dev0 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4