populism_model81 / 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_model81
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_model81
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: 0.2954
- Accuracy: 0.9270
- F1: 0.368
- Recall: 0.6765
- Precision: 0.2527
## 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 | 34 | 0.4249 | 0.9686 | 0.0 | 0.0 | 0.0 |
| 0.4338 | 2.0 | 68 | 0.3313 | 0.9575 | 0.3784 | 0.4118 | 0.35 |
| 0.2741 | 3.0 | 102 | 0.3236 | 0.9482 | 0.3913 | 0.5294 | 0.3103 |
| 0.2741 | 4.0 | 136 | 0.2919 | 0.9298 | 0.3770 | 0.6765 | 0.2614 |
| 0.2314 | 5.0 | 170 | 0.2954 | 0.9270 | 0.368 | 0.6765 | 0.2527 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0