populism_model332 / README.md
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---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model332
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_model332
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_uncased](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3501
- Accuracy: 0.8182
- 1-f1: 0.8378
- 1-recall: 0.9394
- 1-precision: 0.7561
- Balanced Acc: 0.8182
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2145 | 1.0 | 33 | 0.3156 | 0.8485 | 0.8649 | 0.9697 | 0.7805 | 0.8485 |
| 0.2078 | 2.0 | 66 | 0.3509 | 0.8182 | 0.8333 | 0.9091 | 0.7692 | 0.8182 |
| 0.1019 | 3.0 | 99 | 0.3279 | 0.8333 | 0.8533 | 0.9697 | 0.7619 | 0.8333 |
| 0.054 | 4.0 | 132 | 0.4026 | 0.8182 | 0.8333 | 0.9091 | 0.7692 | 0.8182 |
| 0.0359 | 5.0 | 165 | 0.3501 | 0.8182 | 0.8378 | 0.9394 | 0.7561 | 0.8182 |
### Framework versions
- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1