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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_model353
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_model353
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: 0.4901
- Accuracy: 0.7826
- 1-f1: 0.8077
- 1-recall: 0.9130
- 1-precision: 0.7241
- Balanced Acc: 0.7826
## 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 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4474 | 1.0 | 2 | 0.5765 | 0.7609 | 0.7660 | 0.7826 | 0.75 | 0.7609 |
| 0.4942 | 2.0 | 4 | 0.5225 | 0.7609 | 0.7843 | 0.8696 | 0.7143 | 0.7609 |
| 0.371 | 3.0 | 6 | 0.5126 | 0.8043 | 0.8302 | 0.9565 | 0.7333 | 0.8043 |
| 0.3912 | 4.0 | 8 | 0.5075 | 0.8043 | 0.8302 | 0.9565 | 0.7333 | 0.8043 |
| 0.3513 | 5.0 | 10 | 0.4901 | 0.7826 | 0.8077 | 0.9130 | 0.7241 | 0.7826 |
### Framework versions
- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
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