AnonymousCS/populism_classifier_415
013
1---2library_name: transformers3license: apache-2.04base_model: google/rembert5tags:6- generated_from_trainer7metrics:8- accuracy9model-index:10- name: populism_classifier_41511 results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# populism_classifier_41518 19This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset.20It achieves the following results on the evaluation set:21- Loss: 1.031622- Accuracy: 0.947523- 1-f1: 0.024- 1-recall: 0.025- 1-precision: 0.026- Balanced Acc: 0.527 28## Model description29 30More information needed31 32## Intended uses & limitations33 34More information needed35 36## Training and evaluation data37 38More information needed39 40## Training procedure41 42### Training hyperparameters43 44The following hyperparameters were used during training:45- learning_rate: 1e-0546- train_batch_size: 1647- eval_batch_size: 3248- seed: 4249- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments50- lr_scheduler_type: linear51- lr_scheduler_warmup_ratio: 0.0652- num_epochs: 2053- mixed_precision_training: Native AMP54 55### Training results56 57| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |58|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:|59| 0.7657 | 1.0 | 167 | 0.5924 | 0.9475 | 0.0 | 0.0 | 0.0 | 0.5 |60| 0.3731 | 2.0 | 334 | 0.5964 | 0.9475 | 0.0 | 0.0 | 0.0 | 0.5 |61| 0.7384 | 3.0 | 501 | 0.7634 | 0.9475 | 0.0 | 0.0 | 0.0 | 0.5 |62| 0.9117 | 4.0 | 668 | 0.7163 | 0.9475 | 0.0 | 0.0 | 0.0 | 0.5 |63| 0.7798 | 5.0 | 835 | 1.1236 | 0.9475 | 0.0 | 0.0 | 0.0 | 0.5 |64| 0.8696 | 6.0 | 1002 | 1.0316 | 0.9475 | 0.0 | 0.0 | 0.0 | 0.5 |65 66 67### Framework versions68 69- Transformers 4.46.370- Pytorch 2.4.1+cu12171- Datasets 3.1.072- Tokenizers 0.20.373 