populism_classifier_060
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: 0.8386
- Accuracy: 0.9484
- 1-f1: 0.5909
- 1-recall: 0.4815
- 1-precision: 0.7647
- Balanced Acc: 0.7345
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 |
|---|---|---|---|---|---|---|---|---|
| 0.3607 | 1.0 | 22 | 0.1948 | 0.8768 | 0.5567 | 1.0 | 0.3857 | 0.9332 |
| 0.1164 | 2.0 | 44 | 0.2013 | 0.9398 | 0.6667 | 0.7778 | 0.5833 | 0.8656 |
| 0.0699 | 3.0 | 66 | 0.1683 | 0.9398 | 0.6957 | 0.8889 | 0.5714 | 0.9165 |
| 0.0583 | 4.0 | 88 | 0.2549 | 0.9570 | 0.7273 | 0.7407 | 0.7143 | 0.8579 |
| 0.0019 | 5.0 | 110 | 0.8386 | 0.9484 | 0.5909 | 0.4815 | 0.7647 | 0.7345 |
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