populism_classifier_bsample_118
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: 0.3835
- Accuracy: 0.8941
- 1-f1: 0.3224
- 1-recall: 0.9423
- 1-precision: 0.1944
- Balanced Acc: 0.9176
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 |
---|---|---|---|---|---|---|---|---|
0.2342 | 1.0 | 38 | 0.3748 | 0.8191 | 0.2212 | 0.9615 | 0.125 | 0.8884 |
0.3346 | 2.0 | 76 | 0.3659 | 0.8155 | 0.2246 | 1.0 | 0.1265 | 0.9052 |
0.4371 | 3.0 | 114 | 0.1916 | 0.8931 | 0.3158 | 0.9231 | 0.1905 | 0.9077 |
0.2013 | 4.0 | 152 | 0.2561 | 0.9224 | 0.3984 | 0.9615 | 0.2513 | 0.9414 |
0.4561 | 5.0 | 190 | 0.3835 | 0.8941 | 0.3224 | 0.9423 | 0.1944 | 0.9176 |
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