| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google-bert/bert-base-multilingual-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - recall |
| | model-index: |
| | - name: populism_model18 |
| | 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_model18 |
| | |
| | This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2610 |
| | - Accuracy: 0.9680 |
| | - F1: 0.5854 |
| | - Recall: 0.6316 |
| | |
| | ## 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: 128 |
| | - eval_batch_size: 128 |
| | - 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: 5 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:| |
| | | No log | 1.0 | 17 | 0.2259 | 0.9361 | 0.5 | 0.8947 | |
| | | No log | 2.0 | 34 | 0.2387 | 0.9211 | 0.4474 | 0.8947 | |
| | | 0.2346 | 3.0 | 51 | 0.2296 | 0.9699 | 0.6522 | 0.7895 | |
| | | 0.2346 | 4.0 | 68 | 0.2206 | 0.9662 | 0.625 | 0.7895 | |
| | | 0.2346 | 5.0 | 85 | 0.2610 | 0.9680 | 0.5854 | 0.6316 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.47.1 |
| | - Pytorch 2.5.1+cu121 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
