---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model110
  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_model110

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: 0.4183
- Accuracy: 0.8586
- 1-f1: 0.2887
- 1-recall: 0.6087
- 1-precision: 0.1892
- Balanced Acc: 0.7398

## 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: 128
- eval_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| No log        | 1.0   | 16   | 0.5475          | 0.6537   | 0.1914 | 0.8696   | 0.1075      | 0.7563       |
| 0.5254        | 2.0   | 32   | 0.4896          | 0.7131   | 0.2308 | 0.9130   | 0.1321      | 0.8081       |
| 0.5254        | 3.0   | 48   | 0.4099          | 0.8607   | 0.2609 | 0.5217   | 0.1739      | 0.6996       |
| 0.4424        | 4.0   | 64   | 0.4653          | 0.9016   | 0.25   | 0.3478   | 0.1951      | 0.6384       |
| 0.3305        | 5.0   | 80   | 0.4183          | 0.8586   | 0.2887 | 0.6087   | 0.1892      | 0.7398       |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0