--- 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_model324 results: [] --- # populism_model324 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: 0.3592 - Accuracy: 0.9653 - 1-f1: 0.5581 - 1-recall: 0.5217 - 1-precision: 0.6 - Balanced Acc: 0.7532 ## 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 OptimizerNames.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: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.4774 | 1.0 | 69 | 0.2374 | 0.9580 | 0.5660 | 0.6522 | 0.5 | 0.8118 | | 0.2898 | 2.0 | 138 | 0.2868 | 0.9689 | 0.6222 | 0.6087 | 0.6364 | 0.7967 | | 0.2156 | 3.0 | 207 | 0.3592 | 0.9653 | 0.5581 | 0.5217 | 0.6 | 0.7532 | ### Framework versions - Transformers 4.49.0.dev0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0