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library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_396
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_396
This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1083
- Accuracy: 0.7386
- 1-f1: 0.3235
- 1-recall: 1.0
- 1-precision: 0.1930
- Balanced Acc: 0.8606
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 1.5026 | 1.0 | 8 | 0.6012 | 0.9489 | 0.5970 | 0.6061 | 0.5882 | 0.7889 |
| 0.0346 | 2.0 | 16 | 1.1961 | 0.6345 | 0.2548 | 1.0 | 0.1460 | 0.8051 |
| 0.0091 | 3.0 | 24 | 0.3012 | 0.9186 | 0.5743 | 0.8788 | 0.4265 | 0.9 |
| 0.0028 | 4.0 | 32 | 0.8006 | 0.7765 | 0.3587 | 1.0 | 0.2185 | 0.8808 |
| 0.0053 | 5.0 | 40 | 1.1083 | 0.7386 | 0.3235 | 1.0 | 0.1930 | 0.8606 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|