| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/rembert |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_405 |
| | 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_405 |
| |
|
| | 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: 0.6718 |
| | - Accuracy: 0.9316 |
| | - 1-f1: 0.0 |
| | - 1-recall: 0.0 |
| | - 1-precision: 0.0 |
| | - Balanced Acc: 0.5 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.5294 | 1.0 | 95 | 0.6951 | 0.4474 | 0.0870 | 0.3846 | 0.0490 | 0.4183 | |
| | | 0.4281 | 2.0 | 190 | 0.7576 | 0.2395 | 0.0707 | 0.4231 | 0.0386 | 0.3245 | |
| | | 0.6661 | 3.0 | 285 | 0.8551 | 0.0684 | 0.1281 | 1.0 | 0.0684 | 0.5 | |
| | | 0.6035 | 4.0 | 380 | 0.6809 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.451 | 5.0 | 475 | 0.6636 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.6474 | 6.0 | 570 | 0.6653 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.8721 | 7.0 | 665 | 0.7759 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.6361 | 8.0 | 760 | 0.6713 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.4965 | 9.0 | 855 | 0.7745 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.8257 | 10.0 | 950 | 0.6718 | 0.9316 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
