populism_classifier_bsample_153
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: 0.8540
- Accuracy: 0.7462
- 1-f1: 0.3759
- 1-recall: 1.0
- 1-precision: 0.2315
- Balanced Acc: 0.8626
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0106 | 1.0 | 6 | 0.8076 | 0.7615 | 0.3810 | 0.96 | 0.2376 | 0.8525 |
| 0.2221 | 2.0 | 12 | 0.6248 | 0.8104 | 0.4364 | 0.96 | 0.2824 | 0.8790 |
| 0.2669 | 3.0 | 18 | 0.5640 | 0.8563 | 0.4946 | 0.92 | 0.3382 | 0.8855 |
| 0.0064 | 4.0 | 24 | 0.8305 | 0.7462 | 0.3759 | 1.0 | 0.2315 | 0.8626 |
| 0.0094 | 5.0 | 30 | 0.8540 | 0.7462 | 0.3759 | 1.0 | 0.2315 | 0.8626 |
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_153
Base model
google-bert/bert-base-multilingual-cased