|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: FacebookAI/xlm-roberta-large |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: populism_classifier_127 |
|
|
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_127 |
|
|
|
|
|
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: 1.4609 |
|
|
- Accuracy: 0.9021 |
|
|
- 1-f1: 0.4074 |
|
|
- 1-recall: 0.4231 |
|
|
- 1-precision: 0.3929 |
|
|
- Balanced Acc: 0.6833 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 16 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 20 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
|
|
| 0.3295 | 1.0 | 82 | 0.4300 | 0.8869 | 0.4932 | 0.6923 | 0.3830 | 0.7980 | |
|
|
| 0.3319 | 2.0 | 164 | 0.6125 | 0.8685 | 0.4557 | 0.6923 | 0.3396 | 0.7880 | |
|
|
| 0.0201 | 3.0 | 246 | 1.4609 | 0.9021 | 0.4074 | 0.4231 | 0.3929 | 0.6833 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.56.0.dev0 |
|
|
- Pytorch 2.8.0+cu126 |
|
|
- Datasets 4.0.0 |
|
|
- Tokenizers 0.21.4 |
|
|
|