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library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_118
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_118
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: 0.3835
- 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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