--- 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_050 results: [] --- # populism_classifier_bsample_050 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: 0.6834 - Accuracy: 0.8230 - 1-f1: 0.3857 - 1-recall: 0.9643 - 1-precision: 0.2411 - Balanced Acc: 0.8893 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.0371 | 1.0 | 7 | 1.0019 | 0.7058 | 0.2741 | 0.9643 | 0.1598 | 0.8271 | | 0.8511 | 2.0 | 14 | 0.5097 | 0.9095 | 0.5217 | 0.8571 | 0.375 | 0.8849 | | 0.0297 | 3.0 | 21 | 0.7293 | 0.7984 | 0.3553 | 0.9643 | 0.2177 | 0.8762 | | 0.0336 | 4.0 | 28 | 0.6834 | 0.8230 | 0.3857 | 0.9643 | 0.2411 | 0.8893 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3