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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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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- precision |
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- recall |
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model-index: |
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- name: bert-base-uncased-finetuned-spam-real |
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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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# bert-base-uncased-finetuned-spam-real |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0342 |
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- Accuracy: 0.9942 |
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- F1: 0.9945 |
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- Precision: 0.9941 |
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- Recall: 0.9949 |
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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: 3.8529031222986405e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 15 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.0418 | 1.0 | 4173 | 0.0471 | 0.9877 | 0.9882 | 0.9950 | 0.9815 | |
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| 0.0186 | 2.0 | 8346 | 0.0394 | 0.9935 | 0.9938 | 0.9938 | 0.9938 | |
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| 0.0096 | 3.0 | 12519 | 0.0342 | 0.9942 | 0.9945 | 0.9941 | 0.9949 | |
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| 0.0059 | 4.0 | 16692 | 0.0421 | 0.9934 | 0.9937 | 0.9958 | 0.9917 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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