--- 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_019 results: [] --- # populism_classifier_bsample_019 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: 0.5788 - Accuracy: 0.8878 - 1-f1: 0.3736 - 1-recall: 0.85 - 1-precision: 0.2394 - Balanced Acc: 0.8697 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.0478 | 1.0 | 6 | 0.6333 | 0.8406 | 0.3077 | 0.9 | 0.1856 | 0.8691 | | 0.0673 | 2.0 | 12 | 0.5091 | 0.8878 | 0.3736 | 0.85 | 0.2394 | 0.8697 | | 0.0451 | 3.0 | 18 | 0.7074 | 0.8386 | 0.3051 | 0.9 | 0.1837 | 0.8680 | | 0.1484 | 4.0 | 24 | 0.5788 | 0.8878 | 0.3736 | 0.85 | 0.2394 | 0.8697 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3