---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_055
  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_055

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4730
- Accuracy: 0.7929
- 1-f1: 0.3636
- 1-recall: 0.8
- 1-precision: 0.2353
- Balanced Acc: 0.7962

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3429        | 1.0   | 22   | 0.5162          | 0.6213   | 0.2644 | 0.92     | 0.1544      | 0.7587       |
| 0.6946        | 2.0   | 44   | 0.4071          | 0.7959   | 0.3429 | 0.72     | 0.225       | 0.7610       |
| 0.9429        | 3.0   | 66   | 0.6878          | 0.9142   | 0.3830 | 0.36     | 0.4091      | 0.6592       |
| 0.1455        | 4.0   | 88   | 0.4730          | 0.7929   | 0.3636 | 0.8      | 0.2353      | 0.7962       |


### Framework versions

- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4