--- library_name: transformers license: apache-2.0 base_model: google/rembert tags: - generated_from_trainer metrics: - accuracy model-index: - name: populism_classifier_bsample_414 results: [] --- # populism_classifier_bsample_414 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: 0.7557 - Accuracy: 0.8251 - 1-f1: 0.3796 - 1-recall: 0.9286 - 1-precision: 0.2385 - Balanced Acc: 0.8737 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| | 0.0119 | 1.0 | 7 | 0.8462 | 0.8909 | 0.4301 | 0.7143 | 0.3077 | 0.8080 | | 0.1522 | 2.0 | 14 | 0.6626 | 0.8807 | 0.4314 | 0.7857 | 0.2973 | 0.8361 | | 0.0223 | 3.0 | 21 | 0.6833 | 0.8457 | 0.4 | 0.8929 | 0.2577 | 0.8678 | | 0.1239 | 4.0 | 28 | 0.7557 | 0.8251 | 0.3796 | 0.9286 | 0.2385 | 0.8737 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3