--- 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_model329 results: [] --- # populism_model329 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: 0.2755 - Accuracy: 0.9788 - 1-f1: 0.7925 - 1-recall: 0.8077 - 1-precision: 0.7778 - Balanced Acc: 0.8977 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.2638 | 1.0 | 65 | 0.3633 | 0.9749 | 0.7347 | 0.6923 | 0.7826 | 0.8411 | | 0.1694 | 2.0 | 130 | 0.2654 | 0.9788 | 0.7925 | 0.8077 | 0.7778 | 0.8977 | | 0.0985 | 3.0 | 195 | 0.2755 | 0.9788 | 0.7925 | 0.8077 | 0.7778 | 0.8977 | ### Framework versions - Transformers 4.49.0.dev0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0