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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_352
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_352
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: 0.1382
- Accuracy: 0.9939
- 1-f1: 0.8929
- 1-recall: 0.8772
- 1-precision: 0.9091
- Balanced Acc: 0.9373
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.188 | 1.0 | 124 | 0.1878 | 0.96 | 0.5269 | 0.7719 | 0.4 | 0.8688 |
| 0.0717 | 2.0 | 248 | 0.1507 | 0.9635 | 0.5663 | 0.8246 | 0.4312 | 0.8961 |
| 0.0532 | 3.0 | 372 | 0.1856 | 0.9792 | 0.6555 | 0.6842 | 0.6290 | 0.8361 |
| 0.0114 | 4.0 | 496 | 0.1190 | 0.9818 | 0.7391 | 0.8947 | 0.6296 | 0.9395 |
| 0.001 | 5.0 | 620 | 0.1292 | 0.9833 | 0.7660 | 0.9474 | 0.6429 | 0.9659 |
| 0.0012 | 6.0 | 744 | 0.1184 | 0.9899 | 0.8333 | 0.8772 | 0.7937 | 0.9352 |
| 0.0013 | 7.0 | 868 | 0.1127 | 0.9853 | 0.7852 | 0.9298 | 0.6795 | 0.9584 |
| 0.0005 | 8.0 | 992 | 0.1341 | 0.9853 | 0.7852 | 0.9298 | 0.6795 | 0.9584 |
| 0.0003 | 9.0 | 1116 | 0.2046 | 0.9909 | 0.8393 | 0.8246 | 0.8545 | 0.9102 |
| 0.0002 | 10.0 | 1240 | 0.1382 | 0.9939 | 0.8929 | 0.8772 | 0.9091 | 0.9373 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|