populism_classifier_bsample_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: 0.5211
- Accuracy: 0.8333
- 1-f1: 0.4138
- 1-recall: 1.0
- 1-precision: 0.2609
- Balanced Acc: 0.9115
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0779 | 1.0 | 6 | 0.9083 | 0.7426 | 0.3137 | 1.0 | 0.1860 | 0.8633 |
| 0.1032 | 2.0 | 12 | 0.4340 | 0.8407 | 0.4144 | 0.9583 | 0.2644 | 0.8958 |
| 0.1326 | 3.0 | 18 | 0.3459 | 0.8676 | 0.46 | 0.9583 | 0.3026 | 0.9102 |
| 0.0207 | 4.0 | 24 | 0.5807 | 0.8064 | 0.3780 | 1.0 | 0.2330 | 0.8971 |
| 0.0392 | 5.0 | 30 | 0.5211 | 0.8333 | 0.4138 | 1.0 | 0.2609 | 0.9115 |
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_148
Base model
google-bert/bert-base-multilingual-cased