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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 |
### Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.1
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