--- 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_bsample_003 results: [] --- # populism_classifier_bsample_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: 0.6809 - Accuracy: 0.7692 - 1-f1: 0.3910 - 1-recall: 0.8667 - 1-precision: 0.2524 - Balanced Acc: 0.8134 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.1154 | 1.0 | 6 | 0.7949 | 0.7322 | 0.3562 | 0.8667 | 0.2241 | 0.7931 | | 0.1149 | 2.0 | 12 | 0.6876 | 0.7578 | 0.3704 | 0.8333 | 0.2381 | 0.7921 | | 0.1005 | 3.0 | 18 | 0.5583 | 0.7977 | 0.4034 | 0.8 | 0.2697 | 0.7988 | | 0.015 | 4.0 | 24 | 0.6372 | 0.7664 | 0.3881 | 0.8667 | 0.25 | 0.8118 | | 0.0281 | 5.0 | 30 | 0.6809 | 0.7692 | 0.3910 | 0.8667 | 0.2524 | 0.8134 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3