| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_111 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # populism_classifier_bsample_111 |
| |
| This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3306 |
| - Accuracy: 0.8813 |
| - 1-f1: 0.3077 |
| - 1-recall: 0.9091 |
| - 1-precision: 0.1852 |
| - Balanced Acc: 0.8948 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.7516 | 1.0 | 10 | 0.6561 | 0.9631 | 0.0 | 0.0 | 0.0 | 0.4959 | |
| | 0.6877 | 2.0 | 20 | 0.5274 | 0.9710 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | 0.6049 | 3.0 | 30 | 0.5956 | 0.8707 | 0.1967 | 0.5455 | 0.12 | 0.7129 | |
| | 0.5518 | 4.0 | 40 | 0.4287 | 0.8206 | 0.2093 | 0.8182 | 0.12 | 0.8194 | |
| | 0.4657 | 5.0 | 50 | 0.5567 | 0.7018 | 0.1630 | 1.0 | 0.0887 | 0.8465 | |
| | 0.5129 | 6.0 | 60 | 0.2019 | 0.9261 | 0.3636 | 0.7273 | 0.2424 | 0.8297 | |
| | 0.4573 | 7.0 | 70 | 0.1564 | 0.8997 | 0.3214 | 0.8182 | 0.2 | 0.8602 | |
| | 0.2978 | 8.0 | 80 | 0.3465 | 0.8971 | 0.3158 | 0.8182 | 0.1957 | 0.8588 | |
| | 0.1075 | 9.0 | 90 | 0.3306 | 0.8813 | 0.3077 | 0.9091 | 0.1852 | 0.8948 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
