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mobilenetv3-blur-detection-v2
MinhLe999/mobilenetv3-blur-detection-v2
mobilenetv3-blur-detection-v2 is a machine learning model from MinhLe999. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- mobilenet_v3_binary
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026
- SHA
- d06c8aa4
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
mobilenetv3-blur-detection-v2
This model is a fine-tuned version of MinhLe999/mobilenetv3-HandwritingStrip-RandImg on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0230
- Accuracy: 0.9892
- Precision: 0.9821
- Recall: 0.9880
- F1: 0.9851
- Roc Auc: 0.9998
Model description
V2 changed preprocessing strategy: Instead of middle cropping, we resized the model to 512 on the smaller edge then resize the other edge with the same ratio then crop it to 512
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- 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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 0.1440 | 1.0 | 231 | 0.0535 | 0.9870 | 1.0 | 0.9641 | 0.9817 | 0.9992 |
| 0.0183 | 2.0 | 462 | 0.0253 | 0.9913 | 0.9880 | 0.9880 | 0.9880 | 0.9996 |
| 0.0223 | 3.0 | 693 | 0.0295 | 0.9913 | 0.9939 | 0.9820 | 0.9880 | 0.9994 |
| 0.0010 | 4.0 | 924 | 0.0230 | 0.9892 | 0.9821 | 0.9880 | 0.9851 | 0.9998 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- Type
- mobilenet_v3_binary
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026