populism_classifier_bsample_350
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: 0.9903
- Accuracy: 0.6917
- 1-f1: 0.2635
- 1-recall: 0.9565
- 1-precision: 0.1528
- Balanced Acc: 0.8160
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0395 | 1.0 | 6 | 0.7784 | 0.7343 | 0.2933 | 0.9565 | 0.1732 | 0.8386 |
| 0.0395 | 2.0 | 12 | 1.1268 | 0.6466 | 0.2378 | 0.9565 | 0.1358 | 0.7921 |
| 0.0651 | 3.0 | 18 | 0.6008 | 0.8095 | 0.3448 | 0.8696 | 0.2151 | 0.8377 |
| 0.0155 | 4.0 | 24 | 1.0325 | 0.6867 | 0.2604 | 0.9565 | 0.1507 | 0.8134 |
| 0.0109 | 5.0 | 30 | 0.9903 | 0.6917 | 0.2635 | 0.9565 | 0.1528 | 0.8160 |
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_350
Base model
google-bert/bert-base-uncased