populism_classifier_bsample_135
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: 0.8033
- Accuracy: 0.8230
- 1-f1: 0.2449
- 1-recall: 0.8
- 1-precision: 0.1446
- Balanced Acc: 0.8119
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0663 | 1.0 | 7 | 0.7328 | 0.8110 | 0.2330 | 0.8 | 0.1364 | 0.8057 |
| 0.0506 | 2.0 | 14 | 0.8629 | 0.7584 | 0.2047 | 0.8667 | 0.1161 | 0.8105 |
| 0.0108 | 3.0 | 21 | 0.7086 | 0.8469 | 0.2381 | 0.6667 | 0.1449 | 0.7601 |
| 0.0225 | 4.0 | 28 | 0.9156 | 0.7919 | 0.2162 | 0.8 | 0.125 | 0.7958 |
| 0.0275 | 5.0 | 35 | 0.8033 | 0.8230 | 0.2449 | 0.8 | 0.1446 | 0.8119 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Downloads last month
- -
Model tree for AnonymousCS/populism_classifier_bsample_135
Base model
google-bert/bert-base-multilingual-cased