---
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_model101
  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_model101

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: 0.1020
- Accuracy: 0.9736
- F1: 0.7660
- Recall: 0.9474
- Precision: 0.6429

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| No log        | 1.0   | 13   | 0.2792          | 0.9639   | 0.5946 | 0.5789 | 0.6111    |
| No log        | 2.0   | 26   | 0.1608          | 0.9736   | 0.7556 | 0.8947 | 0.6538    |
| No log        | 3.0   | 39   | 0.1047          | 0.9736   | 0.7755 | 1.0    | 0.6333    |
| 0.258         | 4.0   | 52   | 0.1319          | 0.9712   | 0.7143 | 0.7895 | 0.6522    |
| 0.258         | 5.0   | 65   | 0.1020          | 0.9736   | 0.7660 | 0.9474 | 0.6429    |


### Framework versions

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