populism_classifier_148
This model is a fine-tuned version of AnonymousCS/populism_multilingual_bert_cased_v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2107
- Accuracy: 0.9832
- 1-f1: 0.8444
- 1-recall: 0.8636
- 1-precision: 0.8261
- Balanced Acc: 0.9267
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: 128
- eval_batch_size: 128
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.2092 | 1.0 | 13 | 0.1390 | 0.9159 | 0.5570 | 1.0 | 0.3860 | 0.9556 |
| 0.1047 | 2.0 | 26 | 0.1211 | 0.9399 | 0.6377 | 1.0 | 0.4681 | 0.9683 |
| 0.035 | 3.0 | 39 | 0.1102 | 0.9688 | 0.7636 | 0.9545 | 0.6364 | 0.9620 |
| 0.0368 | 4.0 | 52 | 0.1452 | 0.9784 | 0.8163 | 0.9091 | 0.7407 | 0.9457 |
| 0.0269 | 5.0 | 65 | 0.2107 | 0.9832 | 0.8444 | 0.8636 | 0.8261 | 0.9267 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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google-bert/bert-base-multilingual-cased