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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_base_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_311
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_bsample_311
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.co/AnonymousCS/populism_english_bert_base_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9230
- Accuracy: 0.8443
- 1-f1: 0.2917
- 1-recall: 0.5676
- 1-precision: 0.1963
- Balanced Acc: 0.7142
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1263 | 1.0 | 9 | 0.9714 | 0.6580 | 0.2113 | 0.8108 | 0.1215 | 0.7298 |
| 0.0912 | 2.0 | 18 | 0.8500 | 0.6916 | 0.2171 | 0.7568 | 0.1267 | 0.7222 |
| 0.0552 | 3.0 | 27 | 1.1121 | 0.6015 | 0.1920 | 0.8378 | 0.1084 | 0.7126 |
| 0.1296 | 4.0 | 36 | 0.8318 | 0.8519 | 0.3022 | 0.5676 | 0.2059 | 0.7182 |
| 0.0362 | 5.0 | 45 | 1.1942 | 0.6244 | 0.2013 | 0.8378 | 0.1144 | 0.7247 |
| 0.0666 | 6.0 | 54 | 0.9230 | 0.8443 | 0.2917 | 0.5676 | 0.1963 | 0.7142 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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