--- library_name: transformers license: apache-2.0 base_model: google/rembert tags: - generated_from_trainer metrics: - accuracy model-index: - name: populism_classifier_bsample_404 results: [] --- # populism_classifier_bsample_404 This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2847 - Accuracy: 0.9625 - 1-f1: 0.5680 - 1-recall: 0.9231 - 1-precision: 0.4103 - Balanced Acc: 0.9433 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.0181 | 1.0 | 19 | 0.2482 | 0.9538 | 0.5161 | 0.9231 | 0.3582 | 0.9388 | | 0.0008 | 2.0 | 38 | 0.2395 | 0.9671 | 0.5949 | 0.9038 | 0.4434 | 0.9363 | | 0.0003 | 3.0 | 57 | 0.2997 | 0.9620 | 0.5647 | 0.9231 | 0.4068 | 0.9431 | | 0.0005 | 4.0 | 76 | 0.2847 | 0.9625 | 0.5680 | 0.9231 | 0.4103 | 0.9433 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3