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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_base_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_360
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_classifier_360
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2510
- Accuracy: 0.9634
- 1-f1: 0.3
- 1-recall: 0.1875
- 1-precision: 0.75
- Balanced Acc: 0.5924
## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3676 | 1.0 | 24 | 0.5290 | 0.9581 | 0.2727 | 0.1875 | 0.5 | 0.5897 |
| 0.1647 | 2.0 | 48 | 0.6139 | 0.9581 | 0.2727 | 0.1875 | 0.5 | 0.5897 |
| 0.1676 | 3.0 | 72 | 0.5173 | 0.9503 | 0.4242 | 0.4375 | 0.4118 | 0.7051 |
| 0.0549 | 4.0 | 96 | 1.1376 | 0.9581 | 0.2 | 0.125 | 0.5 | 0.5598 |
| 0.0569 | 5.0 | 120 | 0.8185 | 0.9424 | 0.3125 | 0.3125 | 0.3125 | 0.6412 |
| 0.0299 | 6.0 | 144 | 1.2510 | 0.9634 | 0.3 | 0.1875 | 0.75 | 0.5924 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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