populism_classifier_399
This model is a fine-tuned version of google/rembert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7803
- Accuracy: 0.9498
- 1-f1: 0.0
- 1-recall: 0.0
- 1-precision: 0.0
- Balanced Acc: 0.5
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: 16
- 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
- lr_scheduler_warmup_ratio: 0.06
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.2624 | 1.0 | 130 | 0.5929 | 0.9498 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.0352 | 2.0 | 260 | 0.7379 | 0.9498 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.949 | 3.0 | 390 | 0.6221 | 0.9498 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7944 | 4.0 | 520 | 0.9258 | 0.9498 | 0.0 | 0.0 | 0.0 | 0.5 |
| 2.0226 | 5.0 | 650 | 0.7104 | 0.9498 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.0582 | 6.0 | 780 | 0.7803 | 0.9498 | 0.0 | 0.0 | 0.0 | 0.5 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google/rembert