--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-base-multilingual-cased tags: - generated_from_trainer metrics: - accuracy - f1 - recall model-index: - name: populism_model13 results: [] --- # populism_model13 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: 0.2739 - Accuracy: 0.9529 - F1: 0.5 - Recall: 0.6429 ## 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: 128 - eval_batch_size: 128 - 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: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:| | No log | 1.0 | 12 | 0.2842 | 0.9110 | 0.3929 | 0.7857 | | No log | 2.0 | 24 | 0.2805 | 0.9450 | 0.4 | 0.5 | | No log | 3.0 | 36 | 0.2851 | 0.9476 | 0.4118 | 0.5 | | No log | 4.0 | 48 | 0.2578 | 0.9424 | 0.4762 | 0.7143 | | 0.3104 | 5.0 | 60 | 0.2739 | 0.9529 | 0.5 | 0.6429 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0