populism_model66 / README.md
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---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: populism_model66
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_model66
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5870
- Accuracy: 0.9114
- F1: 0.4412
- Recall: 0.5556
- Precision: 0.3659
## 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: 128
- eval_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| No log | 1.0 | 14 | 0.7047 | 0.9301 | 0.25 | 0.1852 | 0.3846 |
| No log | 2.0 | 28 | 0.3870 | 0.8974 | 0.4634 | 0.7037 | 0.3455 |
| No log | 3.0 | 42 | 0.4250 | 0.8765 | 0.4045 | 0.6667 | 0.2903 |
| 0.3082 | 4.0 | 56 | 0.6455 | 0.9184 | 0.3860 | 0.4074 | 0.3667 |
| 0.3082 | 5.0 | 70 | 0.5870 | 0.9114 | 0.4412 | 0.5556 | 0.3659 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0