avid-sponge-222

BeckerAnas/avid-sponge-222

avid-sponge-222 is a image classification model from BeckerAnas. 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. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: convnext
Access: Public
Created: Jun 4, 2025
Updated: Jun 5, 2025
SHA: 7a6c5642

Base models

facebook/convnext-base-224

Model card

From the Hugging Face model README

avid-sponge-222

This model is a fine-tuned version of facebook/convnext-base-224 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1207
Accuracy: 0.9622
Precision: 0.9631
Recall: 0.9622
F1: 0.9622
Roc Auc: 0.9955

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: 0.0001
train_batch_size: 256
eval_batch_size: 256
seed: 42
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
1.3883	1.0	17	1.3638	0.1615	0.5315	0.1615	0.1912	0.6131
1.3166	2.0	34	1.2597	0.4622	0.7044	0.4622	0.3777	0.7535
1.1663	3.0	51	1.1127	0.4193	0.6134	0.4193	0.4666	0.7785
0.9862	4.0	68	0.8247	0.5508	0.6135	0.5508	0.5663	0.8250
0.8022	5.0	85	0.6888	0.5417	0.6930	0.5417	0.5632	0.8414
0.6688	6.0	102	0.6198	0.5729	0.7049	0.5729	0.5936	0.8612
0.5649	7.0	119	0.5550	0.6406	0.7094	0.6406	0.6527	0.8871
0.4652	8.0	136	0.4299	0.7253	0.7475	0.7253	0.7265	0.9158
0.3992	9.0	153	0.4714	0.7174	0.8030	0.7174	0.7161	0.9347
0.2838	10.0	170	0.3594	0.7734	0.7821	0.7734	0.7703	0.9419
0.2476	11.0	187	0.3371	0.7747	0.8446	0.7747	0.7716	0.9623
0.1873	12.0	204	0.5076	0.7018	0.7728	0.7018	0.7099	0.9409
0.1933	13.0	221	0.2128	0.8490	0.8705	0.8490	0.8479	0.9800
0.1069	14.0	238	0.1805	0.8971	0.9041	0.8971	0.8980	0.9857
0.0932	15.0	255	0.2421	0.8385	0.8782	0.8385	0.8355	0.9894
0.1033	16.0	272	0.1561	0.9258	0.9307	0.9258	0.9247	0.9936
0.0343	17.0	289	0.1213	0.9531	0.9537	0.9531	0.9531	0.9954
0.0603	18.0	306	0.1270	0.9336	0.9358	0.9336	0.9338	0.9929
0.0325	19.0	323	0.0917	0.9661	0.9672	0.9661	0.9663	0.9975
0.028	20.0	340	0.1041	0.9453	0.9492	0.9453	0.9456	0.9968
0.0283	21.0	357	0.0671	0.9674	0.9675	0.9674	0.9674	0.9968
0.0098	22.0	374	0.0663	0.9635	0.9657	0.9635	0.9638	0.9976
0.0175	23.0	391	0.0669	0.9727	0.9730	0.9727	0.9727	0.9973
0.0106	24.0	408	0.1230	0.9622	0.9626	0.9622	0.9623	0.9950
0.0227	25.0	425	0.0757	0.9596	0.9612	0.9596	0.9599	0.9978
0.0183	26.0	442	0.1207	0.9622	0.9631	0.9622	0.9622	0.9955

Framework versions

Transformers 4.52.3
Pytorch 2.7.0+cpu
Datasets 3.6.0
Tokenizers 0.21.0

Task: Image Classification
Library: transformers
Type: convnext
License: apache-2.0
Created: Jun 4, 2025
Updated: Jun 5, 2025