populism_classifier_053
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6104
- Accuracy: 0.9181
- 1-f1: 0.3401
- 1-recall: 0.4421
- 1-precision: 0.2763
- Balanced Acc: 0.6920
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.5451 | 1.0 | 871 | 0.4797 | 0.9077 | 0.2743 | 0.3654 | 0.2195 | 0.6501 |
| 0.3057 | 2.0 | 1742 | 0.4281 | 0.8785 | 0.2995 | 0.5444 | 0.2066 | 0.7198 |
| 0.1428 | 3.0 | 2613 | 0.4528 | 0.9120 | 0.3322 | 0.4586 | 0.2605 | 0.6967 |
| 0.1982 | 4.0 | 3484 | 0.6104 | 0.9181 | 0.3401 | 0.4421 | 0.2763 | 0.6920 |
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
answerdotai/ModernBERT-base