---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_365
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_bsample_365

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_large_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8616
- Accuracy: 0.7503
- 1-f1: 0.2609
- 1-recall: 0.9233
- 1-precision: 0.1519
- Balanced Acc: 0.8325

## 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: 32
- eval_batch_size: 32
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1998        | 1.0   | 167  | 1.0855          | 0.4383   | 0.1436 | 0.9865   | 0.0774      | 0.6986       |
| 0.1837        | 2.0   | 334  | 0.8375          | 0.5827   | 0.1811 | 0.9669   | 0.0999      | 0.7652       |
| 0.2009        | 3.0   | 501  | 1.0069          | 0.5708   | 0.1747 | 0.9519   | 0.0962      | 0.7518       |
| 0.1606        | 4.0   | 668  | 0.6591          | 0.7428   | 0.2474 | 0.8857   | 0.1438      | 0.8107       |
| 0.195         | 5.0   | 835  | 0.7884          | 0.7467   | 0.2528 | 0.8977   | 0.1471      | 0.8184       |
| 0.048         | 6.0   | 1002 | 0.8616          | 0.7503   | 0.2609 | 0.9233   | 0.1519      | 0.8325       |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3