populism_classifier_bsample_412
This model is a fine-tuned version of google/rembert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7918
- Accuracy: 0.7150
- 1-f1: 0.2162
- 1-recall: 1.0
- 1-precision: 0.1212
- Balanced Acc: 0.8517
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: 32
- eval_batch_size: 32
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.0566 | 1.0 | 4 | 1.1299 | 0.6585 | 0.1871 | 1.0 | 0.1032 | 0.8223 |
| 0.0665 | 2.0 | 8 | 0.8764 | 0.7224 | 0.2207 | 1.0 | 0.1240 | 0.8555 |
| 0.0703 | 3.0 | 12 | 0.5920 | 0.8034 | 0.2857 | 1.0 | 0.1667 | 0.8977 |
| 0.0455 | 4.0 | 16 | 0.5149 | 0.8256 | 0.2970 | 0.9375 | 0.1765 | 0.8792 |
| 0.0567 | 5.0 | 20 | 0.9592 | 0.7076 | 0.2119 | 1.0 | 0.1185 | 0.8478 |
| 0.025 | 6.0 | 24 | 0.7918 | 0.7150 | 0.2162 | 1.0 | 0.1212 | 0.8517 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for AnonymousCS/populism_classifier_bsample_412
Base model
google/rembert