mobilenetv3-handwriting-blur

This model is a fine-tuned version of on a private dataset. Used to detect images with handwriting for document classification task. It achieves the following results on the evaluation set:

• Loss: 0.0649
• Model Preparation Time: 0.0057
• Accuracy: 0.9763

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: 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: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Accuracy
0.162	1.0	190	0.0816	0.0057	0.9736
0.008	2.0	380	0.0649	0.0057	0.9763

Framework versions

• Transformers 4.57.6
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.2