populism_classifier_bsample_140
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: 0.7158
- Accuracy: 0.8657
- 1-f1: 0.2642
- 1-recall: 0.84
- 1-precision: 0.1567
- Balanced Acc: 0.8532
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0246 | 1.0 | 9 | 0.6186 | 0.8473 | 0.2400 | 0.84 | 0.14 | 0.8438 |
| 0.0605 | 2.0 | 18 | 0.7402 | 0.8266 | 0.2256 | 0.88 | 0.1294 | 0.8525 |
| 0.0036 | 3.0 | 27 | 0.5000 | 0.8955 | 0.3158 | 0.84 | 0.1944 | 0.8686 |
| 0.0333 | 4.0 | 36 | 0.8129 | 0.8312 | 0.2383 | 0.92 | 0.1369 | 0.8743 |
| 0.0009 | 5.0 | 45 | 0.7158 | 0.8657 | 0.2642 | 0.84 | 0.1567 | 0.8532 |
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