populism_classifier_bsample_240
This model is a fine-tuned version of AnonymousCS/populism_multilingual_roberta_base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9436
- Accuracy: 0.7955
- 1-f1: 0.3415
- 1-recall: 0.8485
- 1-precision: 0.2137
- Balanced Acc: 0.8202
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0519 | 1.0 | 8 | 0.8375 | 0.7765 | 0.3218 | 0.8485 | 0.1986 | 0.8101 |
| 0.015 | 2.0 | 16 | 1.0175 | 0.7008 | 0.2818 | 0.9394 | 0.1658 | 0.8121 |
| 0.0228 | 3.0 | 24 | 0.6612 | 0.8371 | 0.3944 | 0.8485 | 0.2569 | 0.8424 |
| 0.0207 | 4.0 | 32 | 0.8965 | 0.7576 | 0.3191 | 0.9091 | 0.1935 | 0.8283 |
| 0.0083 | 5.0 | 40 | 0.9436 | 0.7955 | 0.3415 | 0.8485 | 0.2137 | 0.8202 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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