--- 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_014 results: [] --- # populism_classifier_bsample_014 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: 0.5016 - Accuracy: 0.8926 - 1-f1: 0.3236 - 1-recall: 0.9615 - 1-precision: 0.1946 - Balanced Acc: 0.9261 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.0629 | 1.0 | 19 | 0.5449 | 0.8577 | 0.2730 | 1.0 | 0.1581 | 0.9269 | | 0.0682 | 2.0 | 38 | 0.3342 | 0.9209 | 0.384 | 0.9231 | 0.2424 | 0.9219 | | 0.0283 | 3.0 | 57 | 0.2584 | 0.9486 | 0.4845 | 0.9038 | 0.3310 | 0.9268 | | 0.0175 | 4.0 | 76 | 0.2812 | 0.9466 | 0.48 | 0.9231 | 0.3243 | 0.9351 | | 0.0126 | 5.0 | 95 | 0.5016 | 0.8926 | 0.3236 | 0.9615 | 0.1946 | 0.9261 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3