populism_classifier_155
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: 0.5242
- Accuracy: 0.9580
- 1-f1: 0.6
- 1-recall: 0.6
- 1-precision: 0.6
- Balanced Acc: 0.7889
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 |
|---|---|---|---|---|---|---|---|---|
| 0.3894 | 1.0 | 21 | 0.2502 | 0.9490 | 0.5854 | 0.6857 | 0.5106 | 0.8247 |
| 0.2343 | 2.0 | 42 | 0.2154 | 0.8831 | 0.4583 | 0.9429 | 0.3028 | 0.9113 |
| 0.1673 | 3.0 | 63 | 0.1986 | 0.9460 | 0.625 | 0.8571 | 0.4918 | 0.9040 |
| 0.0636 | 4.0 | 84 | 0.4899 | 0.9625 | 0.6154 | 0.5714 | 0.6667 | 0.7778 |
| 0.0671 | 5.0 | 105 | 0.5242 | 0.9580 | 0.6 | 0.6 | 0.6 | 0.7889 |
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