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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-cased |
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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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- f1 |
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- recall |
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model-index: |
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- name: populism_model5 |
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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_model5 |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5689 |
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- Accuracy: 0.9485 |
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- F1: 0.4444 |
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- Recall: 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-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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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- num_epochs: 5 |
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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 | F1 | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:| |
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| No log | 1.0 | 25 | 0.3309 | 0.8866 | 0.3125 | 0.625 | |
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| 0.3485 | 2.0 | 50 | 0.5070 | 0.9485 | 0.375 | 0.375 | |
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| 0.3485 | 3.0 | 75 | 0.4961 | 0.9381 | 0.4 | 0.5 | |
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| 0.178 | 4.0 | 100 | 0.5562 | 0.9510 | 0.3871 | 0.375 | |
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| 0.178 | 5.0 | 125 | 0.5689 | 0.9485 | 0.4444 | 0.5 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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