---
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_model90
  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_model90

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: 0.7308
- Accuracy: 0.9179
- F1: 0.4335
- Recall: 0.5116
- Precision: 0.3761

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.3922        | 1.0   | 88   | 0.3904          | 0.8769   | 0.4062 | 0.6860 | 0.2885    |
| 0.2731        | 2.0   | 176  | 0.7119          | 0.9347   | 0.3960 | 0.3488 | 0.4580    |
| 0.2129        | 3.0   | 264  | 0.4806          | 0.9040   | 0.4035 | 0.5291 | 0.3262    |
| 0.1491        | 4.0   | 352  | 0.6170          | 0.9162   | 0.4226 | 0.5    | 0.3660    |
| 0.1097        | 5.0   | 440  | 0.7308          | 0.9179   | 0.4335 | 0.5116 | 0.3761    |


### Framework versions

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