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--- |
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license: apache-2.0 |
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base_model: BothBosu/distilbert-scam-classification-v1 |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: distilbert-scam-classification-fine-tuned-elder |
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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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# distilbert-scam-classification-fine-tuned-elder |
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This model is a fine-tuned version of [BothBosu/distilbert-scam-classification-v1](https://huggingface.co/BothBosu/distilbert-scam-classification-v1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6626 |
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- Accuracy: 0.925 |
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- Precision: 0.8889 |
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- Recall: 0.9412 |
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- F1: 0.9143 |
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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: 0.004 |
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- train_batch_size: 64 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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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- training_steps: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.0 | 6.6667 | 20 | 1.8102 | 0.9 | 0.8421 | 0.9412 | 0.8889 | |
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| 0.0 | 13.3333 | 40 | 1.7751 | 0.9 | 0.8421 | 0.9412 | 0.8889 | |
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| 0.0 | 20.0 | 60 | 1.7390 | 0.9 | 0.8421 | 0.9412 | 0.8889 | |
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| 0.0 | 26.6667 | 80 | 1.7140 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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| 0.0 | 33.3333 | 100 | 1.7016 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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| 0.0 | 40.0 | 120 | 1.6990 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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| 0.0 | 46.6667 | 140 | 1.6819 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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| 0.0 | 53.3333 | 160 | 1.6602 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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| 0.0 | 60.0 | 180 | 1.6626 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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| 0.0 | 66.6667 | 200 | 1.6626 | 0.925 | 0.8889 | 0.9412 | 0.9143 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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