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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_333
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_333
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_cased](https://huggingface.co/AnonymousCS/populism_english_bert_large_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2211
- Accuracy: 0.6478
- 1-f1: 0.3417
- 1-recall: 0.8947
- 1-precision: 0.2112
- Balanced Acc: 0.7572
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0935 | 1.0 | 6 | 1.0473 | 0.6640 | 0.3655 | 0.9474 | 0.2264 | 0.7896 |
| 0.0736 | 2.0 | 12 | 1.0857 | 0.7473 | 0.3896 | 0.7895 | 0.2586 | 0.7660 |
| 0.4208 | 3.0 | 18 | 1.0061 | 0.6398 | 0.3431 | 0.9211 | 0.2108 | 0.7644 |
| 0.0248 | 4.0 | 24 | 1.2302 | 0.5269 | 0.3016 | 1.0 | 0.1776 | 0.7365 |
| 0.0268 | 5.0 | 30 | 0.9745 | 0.6317 | 0.3445 | 0.9474 | 0.2105 | 0.7716 |
| 0.035 | 6.0 | 36 | 1.3112 | 0.5995 | 0.3318 | 0.9737 | 0.2 | 0.7653 |
| 0.0158 | 7.0 | 42 | 1.2211 | 0.6478 | 0.3417 | 0.8947 | 0.2112 | 0.7572 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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