mobilenetv3-HandwritingStrip-3class-v1

MinhLe999/mobilenetv3-HandwritingStrip-3class-v1

mobilenetv3-HandwritingStrip-3class-v1 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. --

Downloads · 30 days

6% of all-time downloads

All-time downloads

Public

Parameters

4.2M

17 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors17 MB · 100%

At a glance

Library: transformers
Model type: mobilenet_v3_binary
Access: Public
Created: Mar 6, 2026
Updated: Mar 6, 2026
SHA: 4a549135

Model card

From the Hugging Face model README

mobilenetv3-HandwritingStrip-3class-v1

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0135
Accuracy: 0.9952
Precision: 0.9960
Recall: 0.9922
F1: 0.9940
Roc Auc: 0.9999

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: 64
eval_batch_size: 64
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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
0.4220	0.0847	10	0.5832	0.7518	0.7690	0.7867	0.7564	0.9486
0.0928	0.1695	20	0.1893	0.9379	0.9250	0.9440	0.9324	0.9908
0.1184	0.2542	30	0.1775	0.9356	0.9194	0.9436	0.9262	0.9944
0.1044	0.3390	40	0.0801	0.9690	0.9587	0.9680	0.9629	0.9980
0.0729	0.4237	50	0.0806	0.9714	0.9607	0.9701	0.9649	0.9973
0.0726	0.5085	60	0.0985	0.9547	0.9395	0.9579	0.9464	0.9979
0.0501	0.5932	70	0.0704	0.9761	0.9656	0.9779	0.9709	0.9982
0.0419	0.6780	80	0.0422	0.9881	0.9828	0.9880	0.9853	0.9993
0.0452	0.7627	90	0.0256	0.9928	0.9920	0.9901	0.9911	0.9998
0.0733	0.8475	100	0.0515	0.9785	0.9689	0.9799	0.9738	0.9991
0.0617	0.9322	110	0.0492	0.9809	0.9846	0.9686	0.9756	0.9997
0.0250	1.0169	120	0.0247	0.9881	0.9843	0.9861	0.9852	0.9997
0.0367	1.1017	130	0.0248	0.9881	0.9843	0.9861	0.9852	0.9998
0.0477	1.1864	140	0.0237	0.9881	0.9861	0.9861	0.9861	0.9997
0.0446	1.2712	150	0.1330	0.9547	0.9389	0.9597	0.9459	0.9983
0.0428	1.3559	160	0.0419	0.9809	0.9747	0.9781	0.9764	0.9994
0.0267	1.4407	170	0.0281	0.9857	0.9792	0.9860	0.9824	0.9997
0.0243	1.5254	180	0.0172	0.9952	0.9941	0.9941	0.9941	1.0000
0.0220	1.6102	190	0.0172	0.9928	0.9921	0.9921	0.9921	0.9999
0.0338	1.6949	200	0.0213	0.9905	0.9882	0.9901	0.9891	0.9999
0.0171	1.7797	210	0.0177	0.9928	0.9902	0.9920	0.9911	0.9999
0.0304	1.8644	220	0.0168	0.9928	0.9920	0.9901	0.9911	0.9999
0.0200	1.9492	230	0.0191	0.9905	0.9900	0.9862	0.9880	0.9999
0.0279	2.0339	240	0.0177	0.9905	0.9900	0.9862	0.9880	0.9999
0.0213	2.1186	250	0.0171	0.9905	0.9900	0.9862	0.9880	0.9999
0.0058	2.2034	260	0.0238	0.9881	0.9843	0.9861	0.9852	0.9998
0.0104	2.2881	270	0.0275	0.9881	0.9843	0.9861	0.9852	0.9998
0.0130	2.3729	280	0.0173	0.9881	0.9843	0.9861	0.9852	0.9998
0.0047	2.4576	290	0.0153	0.9928	0.9940	0.9882	0.9910	0.9999
0.0096	2.5424	300	0.0160	0.9928	0.9940	0.9882	0.9910	0.9999
0.0139	2.6271	310	0.0155	0.9928	0.9940	0.9882	0.9910	0.9999
0.0129	2.7119	320	0.0149	0.9928	0.9940	0.9882	0.9910	0.9999
0.0106	2.7966	330	0.0143	0.9928	0.9940	0.9882	0.9910	0.9999
0.0136	2.8814	340	0.0137	0.9952	0.9960	0.9922	0.9940	0.9999
0.0194	2.9661	350	0.0135	0.9952	0.9960	0.9922	0.9940	0.9999

Framework versions

Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Library: transformers
Type: mobilenet_v3_binary
Created: Mar 6, 2026
Updated: Mar 6, 2026