--- 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_bsample_043 results: [] --- # populism_classifier_bsample_043 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: 0.8835 - Accuracy: 0.7745 - 1-f1: 0.2581 - 1-recall: 0.9091 - 1-precision: 0.1504 - Balanced Acc: 0.8388 ## 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: 32 - eval_batch_size: 32 - 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: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.207 | 1.0 | 7 | 1.4555 | 0.6294 | 0.1747 | 0.9091 | 0.0966 | 0.7629 | | 0.2507 | 2.0 | 14 | 0.6206 | 0.8490 | 0.2936 | 0.7273 | 0.1839 | 0.7909 | | 0.0579 | 3.0 | 21 | 1.0325 | 0.7137 | 0.2151 | 0.9091 | 0.1220 | 0.8070 | | 0.0481 | 4.0 | 28 | 0.8835 | 0.7745 | 0.2581 | 0.9091 | 0.1504 | 0.8388 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3