populism_classifier_bsample_409
This model is a fine-tuned version of google/rembert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6809
- Accuracy: 0.9114
- 1-f1: 0.4444
- 1-recall: 0.9
- 1-precision: 0.2951
- Balanced Acc: 0.9059
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0569 | 1.0 | 6 | 0.5669 | 0.8287 | 0.304 | 0.95 | 0.1810 | 0.8869 |
| 0.0356 | 2.0 | 12 | 0.4316 | 0.9075 | 0.4337 | 0.9 | 0.2857 | 0.9039 |
| 0.0073 | 3.0 | 18 | 0.5107 | 0.9213 | 0.4737 | 0.9 | 0.3214 | 0.9111 |
| 0.0007 | 4.0 | 24 | 0.6809 | 0.9114 | 0.4444 | 0.9 | 0.2951 | 0.9059 |
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_409
Base model
google/rembert