convnextv2-base-22k-384-finetuned-humid-classes-19

dacunaq/convnextv2-base-22k-384-finetuned-humid-classes-19

convnextv2-base-22k-384-finetuned-humid-classes-19 is a image classification model from dacunaq. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

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

Downloads · 30 days

4% of all-time downloads

All-time downloads

249

Public

Parameters

87.7M

9.5 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors351 MB · 100%

At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: convnextv2
Access: Public
Created: Nov 6, 2025
Updated: Nov 6, 2025
SHA: 72fc8f72

Base models

facebook/convnextv2-base-22k-384

Datasets

imagefolder

Model card

From the Hugging Face model README

convnextv2-base-22k-384-finetuned-humid-classes-19

This model is a fine-tuned version of facebook/convnextv2-base-22k-384 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0484
Accuracy: 1.0
F1 Macro: 1.0
Precision Macro: 1.0
Recall Macro: 1.0
Precision Dry: 1.0
Recall Dry: 1.0
F1 Dry: 1.0
Precision Rockies: 1.0
Recall Rockies: 1.0
F1 Rockies: 1.0

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Precision Macro	Recall Macro	Precision Dry	Recall Dry	F1 Dry	Precision Rockies	Recall Rockies	F1 Rockies
No log	1.0	3	0.6896	0.4375	0.4353	0.4833	0.4818	0.6667	0.3636	0.4706	0.3	0.6	0.4
No log	2.0	6	0.3815	0.875	0.8333	0.9231	0.8	0.8462	1.0	0.9167	1.0	0.6	0.75
No log	3.0	9	0.1724	0.9375	0.9227	0.9583	0.9	0.9167	1.0	0.9565	1.0	0.8	0.8889
0.5491	4.0	12	0.0484	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.5491	5.0	15	0.0112	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.5491	6.0	18	0.0027	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0442	7.0	21	0.0008	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0442	8.0	24	0.0003	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0442	9.0	27	0.0002	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0007	10.0	30	0.0009	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0007	11.0	33	0.0001	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0007	12.0	36	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0007	13.0	39	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	14.0	42	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	15.0	45	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	16.0	48	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	17.0	51	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	18.0	54	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	19.0	57	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	20.0	60	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	21.0	63	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	22.0	66	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	23.0	69	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	24.0	72	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	25.0	75	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	26.0	78	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	27.0	81	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	28.0	84	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	29.0	87	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	30.0	90	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	31.0	93	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	32.0	96	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	33.0	99	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	34.0	102	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	35.0	105	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	36.0	108	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	37.0	111	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	38.0	114	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	39.0	117	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	40.0	120	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	41.0	123	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	42.0	126	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	43.0	129	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	44.0	132	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	45.0	135	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	46.0	138	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	47.0	141	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	48.0	144	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	49.0	147	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
0.0	50.0	150	0.0000	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0

Task: Image Classification
Library: transformers
Type: convnextv2
License: apache-2.0
Created: Nov 6, 2025
Updated: Nov 6, 2025