| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/mobilebert-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: xdefender-edge-sms |
| 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. --> |
|
|
| # xdefender-edge-sms |
|
|
| This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 137548.8125 |
| - Accuracy: 0.6154 |
| - Precision: 0.6154 |
| - Recall: 1.0 |
| - F1: 0.7619 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 13 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 2062021.6 | 1.0 | 13 | 850877.375 | 0.3846 | 0.0 | 0.0 | 0.0 | |
| | 660729.65 | 2.0 | 26 | 150588.2344 | 0.6154 | 0.6154 | 1.0 | 0.7619 | |
| | 111387.95 | 3.0 | 39 | 4234.5283 | 0.5385 | 0.6429 | 0.5625 | 0.6 | |
| | 5760.7262 | 4.0 | 52 | 2093.7539 | 0.4231 | 1.0 | 0.0625 | 0.1176 | |
| | 2538.1734 | 5.0 | 65 | 202.3052 | 0.3077 | 0.0 | 0.0 | 0.0 | |
| | 1129.3242 | 6.0 | 78 | 91.8728 | 0.6154 | 0.6154 | 1.0 | 0.7619 | |
| | 205.6373 | 7.0 | 91 | 15.5296 | 0.3846 | 0.0 | 0.0 | 0.0 | |
| | 30.6633 | 8.0 | 104 | 3.3818 | 0.6154 | 0.6154 | 1.0 | 0.7619 | |
| | 3.7607 | 9.0 | 117 | 1.7103 | 0.3846 | 0.0 | 0.0 | 0.0 | |
| | 1.1705 | 10.0 | 130 | 0.7337 | 0.4615 | 1.0 | 0.125 | 0.2222 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.16.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 5.0.1 |
| - Tokenizers 0.23.1 |
|
|
