metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_094
results: []
populism_classifier_bsample_094
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1885
- Accuracy: 0.7463
- 1-f1: 0.4138
- 1-recall: 0.96
- 1-precision: 0.2637
- Balanced Acc: 0.8421
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 |
|---|---|---|---|---|---|---|---|---|
| 0.3505 | 1.0 | 8 | 0.9683 | 0.8097 | 0.4516 | 0.84 | 0.3088 | 0.8233 |
| 0.2061 | 2.0 | 16 | 1.8223 | 0.6493 | 0.3380 | 0.96 | 0.2051 | 0.7886 |
| 0.1014 | 3.0 | 24 | 1.1885 | 0.7463 | 0.4138 | 0.96 | 0.2637 | 0.8421 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3