--- 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_classifier_bsample_032 results: [] --- # populism_classifier_bsample_032 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: 0.6975 - Accuracy: 0.8125 - 1-f1: 0.3851 - 1-recall: 0.9394 - 1-precision: 0.2422 - Balanced Acc: 0.8717 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.0138 | 1.0 | 8 | 0.7747 | 0.75 | 0.3265 | 0.9697 | 0.1963 | 0.8525 | | 0.0265 | 2.0 | 16 | 0.7617 | 0.7803 | 0.3409 | 0.9091 | 0.2098 | 0.8404 | | 0.0489 | 3.0 | 24 | 0.6448 | 0.8598 | 0.3934 | 0.7273 | 0.2697 | 0.7980 | | 0.0109 | 4.0 | 32 | 0.7026 | 0.7973 | 0.3669 | 0.9394 | 0.2279 | 0.8636 | | 0.0057 | 5.0 | 40 | 0.6975 | 0.8125 | 0.3851 | 0.9394 | 0.2422 | 0.8717 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3