populism_classifier_bsample_121
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7296
- Accuracy: 0.8706
- 1-f1: 0.2667
- 1-recall: 0.5455
- 1-precision: 0.1765
- Balanced Acc: 0.7154
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
---|---|---|---|---|---|---|---|---|
0.8174 | 1.0 | 13 | 0.7155 | 0.6765 | 0.1538 | 0.6818 | 0.0867 | 0.6790 |
0.5917 | 2.0 | 26 | 0.9101 | 0.4471 | 0.1076 | 0.7727 | 0.0578 | 0.6026 |
0.6631 | 3.0 | 39 | 0.6485 | 0.7941 | 0.1860 | 0.5455 | 0.1121 | 0.6754 |
0.7637 | 4.0 | 52 | 1.0171 | 0.4510 | 0.1083 | 0.7727 | 0.0582 | 0.6046 |
0.7074 | 5.0 | 65 | 0.7296 | 0.8706 | 0.2667 | 0.5455 | 0.1765 | 0.7154 |
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
FacebookAI/xlm-roberta-large