populism_classifier_003
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2029
- Accuracy: 0.9704
- 1-f1: 0.8214
- 1-recall: 0.92
- 1-precision: 0.7419
- Balanced Acc: 0.9472
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 OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|---|---|---|---|---|
| 0.2206 | 1.0 | 11 | 0.1905 | 0.9645 | 0.7857 | 0.88 | 0.7097 | 0.9256 |
| 0.2774 | 2.0 | 22 | 0.1687 | 0.9675 | 0.8070 | 0.92 | 0.7188 | 0.9456 |
| 0.0912 | 3.0 | 33 | 0.1892 | 0.9675 | 0.8 | 0.88 | 0.7333 | 0.9272 |
| 0.0528 | 4.0 | 44 | 0.2029 | 0.9704 | 0.8214 | 0.92 | 0.7419 | 0.9472 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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Base model
google-bert/bert-base-multilingual-cased