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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_bsample_368
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_368
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: 0.8315
- Accuracy: 0.7876
- 1-f1: 0.1382
- 1-recall: 0.8571
- 1-precision: 0.0752
- Balanced Acc: 0.8217
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2135 | 1.0 | 15 | 0.6091 | 0.7643 | 0.1189 | 0.8 | 0.0642 | 0.7818 |
| 0.1079 | 2.0 | 30 | 0.6023 | 0.7450 | 0.1074 | 0.7714 | 0.0577 | 0.7580 |
| 0.0897 | 3.0 | 45 | 0.8614 | 0.7405 | 0.1092 | 0.8 | 0.0586 | 0.7696 |
| 0.4058 | 4.0 | 60 | 0.5266 | 0.8671 | 0.1583 | 0.6286 | 0.0905 | 0.7503 |
| 0.169 | 5.0 | 75 | 0.6161 | 0.8348 | 0.1516 | 0.7429 | 0.0844 | 0.7897 |
| 0.0128 | 6.0 | 90 | 0.8315 | 0.7876 | 0.1382 | 0.8571 | 0.0752 | 0.8217 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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