---
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_model92
  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_model92

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: 0.5724
- Accuracy: 0.9193
- F1: 0.5015
- Recall: 0.6613
- Precision: 0.4039

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.3745        | 1.0   | 64   | 0.3523          | 0.8727   | 0.4376 | 0.8065 | 0.3003    |
| 0.2958        | 2.0   | 128  | 0.3617          | 0.8668   | 0.4361 | 0.8387 | 0.2946    |
| 0.235         | 3.0   | 192  | 0.4251          | 0.8990   | 0.4769 | 0.75   | 0.3496    |
| 0.1525        | 4.0   | 256  | 0.6327          | 0.9386   | 0.5079 | 0.5161 | 0.5       |
| 0.1012        | 5.0   | 320  | 0.5724          | 0.9193   | 0.5015 | 0.6613 | 0.4039    |


### Framework versions

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