natix-001

EchoFox0829/natix-001

natix-001 is a image classification model from EchoFox0829. Use it when you need a label for an image. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
Model type: vit
Access: Public
Created: Nov 19, 2025
Updated: Dec 1, 2025
SHA: 12d096ae

Base models

hayden-yuma/roadwork

Model card

From the Hugging Face model README

natix-001

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

Loss: 0.2443
Accuracy: 0.9753
None Accuracy: 0.9264
Roadwork Accuracy: 0.9878

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 1000
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	None Accuracy	Roadwork Accuracy
0.1454	1.0	3966	0.1717	0.9451	0.9107	0.9540
0.0527	2.0	7932	0.1607	0.9627	0.8960	0.9798
0.0643	3.0	11898	0.1583	0.9638	0.9283	0.9728
0.0379	4.0	15864	0.2043	0.9683	0.9084	0.9836
0.0145	5.0	19830	0.1901	0.9671	0.9359	0.9751
0.0248	6.0	23796	0.2259	0.9696	0.9240	0.9813
0.0158	7.0	27762	0.2219	0.9717	0.9292	0.9825
0.018	8.0	31728	0.2804	0.9720	0.9113	0.9876
0.019	9.0	35694	0.2698	0.9727	0.9207	0.9861
0.0056	10.0	39660	0.2698	0.9727	0.9218	0.9857
0.0228	11.0	43626	0.3909	0.9613	0.8351	0.9937
0.0394	12.0	47592	0.1928	0.9680	0.9252	0.9789
0.0302	13.0	51558	0.1897	0.9707	0.9193	0.9838
0.0143	14.0	55524	0.2491	0.9716	0.8999	0.9899
0.0157	15.0	59490	0.2214	0.9728	0.9331	0.9830
0.0214	16.0	63456	0.2423	0.9745	0.9238	0.9874
0.0251	17.0	67422	0.2447	0.9746	0.9217	0.9882
0.0183	18.0	71388	0.2443	0.9753	0.9264	0.9878
0.0181	19.0	75354	0.2839	0.9748	0.9169	0.9897
0.0211	20.0	79320	0.2739	0.9747	0.9201	0.9887

Framework versions

Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

Task: Image Classification
Library: transformers
Type: vit
Created: Nov 19, 2025
Updated: Dec 1, 2025