---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: populism_model91
  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_model91

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: 0.4717
- Accuracy: 0.8816
- F1: 0.3699
- Recall: 0.6575
- Precision: 0.2574

## 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 | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.4647        | 1.0   | 87   | 0.4302          | 0.7715   | 0.2739 | 0.8151 | 0.1646    |
| 0.3772        | 2.0   | 174  | 0.4315          | 0.7433   | 0.2698 | 0.8973 | 0.1588    |
| 0.3202        | 3.0   | 261  | 0.4559          | 0.9120   | 0.3910 | 0.5342 | 0.3083    |
| 0.2932        | 4.0   | 348  | 0.4034          | 0.8642   | 0.3612 | 0.7260 | 0.2404    |
| 0.2481        | 5.0   | 435  | 0.4717          | 0.8816   | 0.3699 | 0.6575 | 0.2574    |


### Framework versions

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