| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/rembert |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_395 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # populism_classifier_395 |
| |
|
| | 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: 0.7593 |
| | - Accuracy: 0.7203 |
| | - 1-f1: 0.1781 |
| | - 1-recall: 0.5417 |
| | - 1-precision: 0.1066 |
| | - Balanced Acc: 0.6363 |
| |
|
| | ## 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: 16 |
| | - 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 |
| | - lr_scheduler_warmup_ratio: 0.06 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.3534 | 1.0 | 108 | 0.6570 | 0.9417 | 0.0 | 0.0 | 0.0 | 0.4988 | |
| | | 0.6423 | 2.0 | 216 | 0.6427 | 0.9417 | 0.0 | 0.0 | 0.0 | 0.4988 | |
| | | 0.6418 | 3.0 | 324 | 0.6813 | 0.7413 | 0.0672 | 0.1667 | 0.0421 | 0.4710 | |
| | | 0.9179 | 4.0 | 432 | 0.9171 | 0.9441 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.6552 | 5.0 | 540 | 0.6415 | 0.9394 | 0.0 | 0.0 | 0.0 | 0.4975 | |
| | | 0.2303 | 6.0 | 648 | 0.9350 | 0.0583 | 0.1062 | 1.0 | 0.0561 | 0.5012 | |
| | | 0.275 | 7.0 | 756 | 0.9327 | 0.0606 | 0.1064 | 1.0 | 0.0562 | 0.5025 | |
| | | 0.0706 | 8.0 | 864 | 0.7735 | 0.7319 | 0.1353 | 0.375 | 0.0826 | 0.5640 | |
| | | 0.0629 | 9.0 | 972 | 0.9589 | 0.5361 | 0.0744 | 0.3333 | 0.0419 | 0.4407 | |
| | | 0.0181 | 10.0 | 1080 | 0.7593 | 0.7203 | 0.1781 | 0.5417 | 0.1066 | 0.6363 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
