metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_123
results: []
populism_classifier_bsample_123
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: 0.6160
- Accuracy: 0.8602
- 1-f1: 0.1647
- 1-recall: 0.35
- 1-precision: 0.1077
- Balanced Acc: 0.6156
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 |
|---|---|---|---|---|---|---|---|---|
| 0.6697 | 1.0 | 11 | 0.5102 | 0.9606 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.754 | 2.0 | 22 | 0.5048 | 0.9429 | 0.0645 | 0.05 | 0.0909 | 0.5148 |
| 0.7323 | 3.0 | 33 | 0.7132 | 0.3366 | 0.0965 | 0.9 | 0.0510 | 0.6068 |
| 0.6716 | 4.0 | 44 | 0.6160 | 0.8602 | 0.1647 | 0.35 | 0.1077 | 0.6156 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3