populism_classifier_bsample_014
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5016
- Accuracy: 0.8926
- 1-f1: 0.3236
- 1-recall: 0.9615
- 1-precision: 0.1946
- Balanced Acc: 0.9261
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0629 | 1.0 | 19 | 0.5449 | 0.8577 | 0.2730 | 1.0 | 0.1581 | 0.9269 |
| 0.0682 | 2.0 | 38 | 0.3342 | 0.9209 | 0.384 | 0.9231 | 0.2424 | 0.9219 |
| 0.0283 | 3.0 | 57 | 0.2584 | 0.9486 | 0.4845 | 0.9038 | 0.3310 | 0.9268 |
| 0.0175 | 4.0 | 76 | 0.2812 | 0.9466 | 0.48 | 0.9231 | 0.3243 | 0.9351 |
| 0.0126 | 5.0 | 95 | 0.5016 | 0.8926 | 0.3236 | 0.9615 | 0.1946 | 0.9261 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-bert/bert-base-multilingual-cased