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--- |
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library_name: transformers |
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license: mit |
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base_model: AnonymousCS/populism_xlmr_base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: populism_classifier_bsample_188 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# populism_classifier_bsample_188 |
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This model is a fine-tuned version of [AnonymousCS/populism_xlmr_base](https://huggingface.co/AnonymousCS/populism_xlmr_base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7677 |
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- Accuracy: 0.0625 |
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- 1-f1: 0.1176 |
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- 1-recall: 1.0 |
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- 1-precision: 0.0625 |
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- Balanced Acc: 0.5 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.06 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
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| 0.7395 | 1.0 | 15 | 0.7633 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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| 0.6978 | 2.0 | 30 | 0.7616 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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| 0.7113 | 3.0 | 45 | 0.7629 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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| 0.705 | 4.0 | 60 | 0.7651 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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| 0.7479 | 5.0 | 75 | 0.7672 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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| 0.6759 | 6.0 | 90 | 0.7664 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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| 0.6576 | 7.0 | 105 | 0.7677 | 0.0625 | 0.1176 | 1.0 | 0.0625 | 0.5 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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