populism_model115
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: 0.3979
- Accuracy: 0.9287
- 1-f1: 0.4179
- 1-recall: 0.5833
- 1-precision: 0.3256
- Balanced Acc: 0.7639
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 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 | 1-f1 | 1-recall | 1-precision | Balanced Acc |
---|---|---|---|---|---|---|---|---|
0.5347 | 1.0 | 35 | 0.4658 | 0.9561 | 0.0 | 0.0 | 0.0 | 0.5 |
0.4651 | 2.0 | 70 | 0.4272 | 0.9543 | 0.1935 | 0.125 | 0.4286 | 0.5587 |
0.4224 | 3.0 | 105 | 0.4009 | 0.8848 | 0.3636 | 0.75 | 0.24 | 0.8205 |
0.4549 | 4.0 | 140 | 0.3999 | 0.8903 | 0.375 | 0.75 | 0.25 | 0.8234 |
0.3738 | 5.0 | 175 | 0.3979 | 0.9287 | 0.4179 | 0.5833 | 0.3256 | 0.7639 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for AnonymousCS/populism_model115
Base model
answerdotai/ModernBERT-base