populism_classifier_363
This model is a fine-tuned version of AnonymousCS/populism_english_bert_base_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9208
- Accuracy: 0.9610
- 1-f1: 0.5
- 1-recall: 0.3714
- 1-precision: 0.7647
- Balanced Acc: 0.6825
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 |
|---|---|---|---|---|---|---|---|---|
| 0.7421 | 1.0 | 42 | 0.5374 | 0.9565 | 0.4314 | 0.3143 | 0.6875 | 0.6532 |
| 0.203 | 2.0 | 84 | 0.3242 | 0.9475 | 0.5783 | 0.6857 | 0.5 | 0.8239 |
| 0.2372 | 3.0 | 126 | 0.4094 | 0.9580 | 0.6216 | 0.6571 | 0.5897 | 0.8159 |
| 0.0244 | 4.0 | 168 | 0.6149 | 0.9535 | 0.5079 | 0.4571 | 0.5714 | 0.7191 |
| 0.047 | 5.0 | 210 | 0.9208 | 0.9610 | 0.5 | 0.3714 | 0.7647 | 0.6825 |
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_363
Base model
google-bert/bert-base-uncased