populism_classifier_bsample_114
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: 0.5910
- Accuracy: 0.8083
- 1-f1: 0.1854
- 1-recall: 0.76
- 1-precision: 0.1056
- Balanced Acc: 0.7848
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 |
---|---|---|---|---|---|---|---|---|
0.7255 | 1.0 | 17 | 0.8048 | 0.2239 | 0.0689 | 1.0 | 0.0357 | 0.6005 |
0.6833 | 2.0 | 34 | 0.6555 | 0.6487 | 0.1307 | 0.92 | 0.0703 | 0.7803 |
0.5222 | 3.0 | 51 | 0.5096 | 0.6441 | 0.1341 | 0.96 | 0.0721 | 0.7974 |
0.5846 | 4.0 | 68 | 0.7016 | 0.6487 | 0.1356 | 0.96 | 0.0729 | 0.7997 |
0.1869 | 5.0 | 85 | 0.5910 | 0.8083 | 0.1854 | 0.76 | 0.1056 | 0.7848 |
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