populism_classifier_bsample_383
This model is a fine-tuned version of AnonymousCS/populism_english_bert_large_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4915
- Accuracy: 0.8839
- 1-f1: 0.3918
- 1-recall: 0.95
- 1-precision: 0.2468
- Balanced Acc: 0.9156
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0075 | 1.0 | 6 | 0.5607 | 0.8307 | 0.3175 | 1.0 | 0.1887 | 0.9119 |
| 0.011 | 2.0 | 12 | 0.4957 | 0.8583 | 0.3571 | 1.0 | 0.2174 | 0.9262 |
| 0.0278 | 3.0 | 18 | 0.3455 | 0.9094 | 0.4390 | 0.9 | 0.2903 | 0.9049 |
| 0.0031 | 4.0 | 24 | 0.3645 | 0.9114 | 0.4578 | 0.95 | 0.3016 | 0.9299 |
| 0.0012 | 5.0 | 30 | 0.4915 | 0.8839 | 0.3918 | 0.95 | 0.2468 | 0.9156 |
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_383
Base model
google-bert/bert-large-uncased