populism_classifier_077
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: 1.8489
- Accuracy: 0.9535
- 1-f1: 0.3111
- 1-recall: 0.2
- 1-precision: 0.7
- Balanced Acc: 0.5976
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 |
---|---|---|---|---|---|---|---|---|
0.7122 | 1.0 | 42 | 0.5482 | 0.9445 | 0.1395 | 0.0857 | 0.375 | 0.5389 |
0.2773 | 2.0 | 84 | 0.5533 | 0.9565 | 0.4314 | 0.3143 | 0.6875 | 0.6532 |
0.1058 | 3.0 | 126 | 0.4948 | 0.9130 | 0.4082 | 0.5714 | 0.3175 | 0.7517 |
0.0171 | 4.0 | 168 | 1.0110 | 0.9445 | 0.3934 | 0.3429 | 0.4615 | 0.6604 |
0.0241 | 5.0 | 210 | 1.8489 | 0.9535 | 0.3111 | 0.2 | 0.7 | 0.5976 |
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