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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_378
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_378
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: 0.2057
- Accuracy: 0.9889
- 1-f1: 0.8103
- 1-recall: 0.8246
- 1-precision: 0.7966
- Balanced Acc: 0.9092
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0473 | 1.0 | 124 | 0.1713 | 0.9559 | 0.5246 | 0.8421 | 0.3810 | 0.9007 |
| 0.0268 | 2.0 | 248 | 0.1379 | 0.9863 | 0.7523 | 0.7193 | 0.7885 | 0.8568 |
| 0.0541 | 3.0 | 372 | 0.1311 | 0.9818 | 0.7353 | 0.8772 | 0.6329 | 0.9310 |
| 0.0025 | 4.0 | 496 | 0.1546 | 0.9934 | 0.8829 | 0.8596 | 0.9074 | 0.9285 |
| 0.0003 | 5.0 | 620 | 0.1866 | 0.9919 | 0.8596 | 0.8596 | 0.8596 | 0.9277 |
| 0.0005 | 6.0 | 744 | 0.2057 | 0.9889 | 0.8103 | 0.8246 | 0.7966 | 0.9092 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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