populism_classifier_249
This model is a fine-tuned version of AnonymousCS/populism_multilingual_roberta_base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5324
- Accuracy: 0.9158
- 1-f1: 0.5429
- 1-recall: 0.7308
- 1-precision: 0.4318
- Balanced Acc: 0.8301
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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.5015 | 1.0 | 24 | 0.5517 | 0.8368 | 0.4259 | 0.8846 | 0.2805 | 0.8590 |
| 0.3587 | 2.0 | 48 | 0.3700 | 0.9105 | 0.5641 | 0.8462 | 0.4231 | 0.8807 |
| 0.1572 | 3.0 | 72 | 0.3893 | 0.9 | 0.5128 | 0.7692 | 0.3846 | 0.8394 |
| 0.1018 | 4.0 | 96 | 0.4481 | 0.9316 | 0.5937 | 0.7308 | 0.5 | 0.8385 |
| 0.1103 | 5.0 | 120 | 0.5324 | 0.9158 | 0.5429 | 0.7308 | 0.4318 | 0.8301 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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