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---
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
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