test-hasy-6

khaingsmon/test-hasy-6

test-hasy-6 is a image classification model from khaingsmon. 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: vit
Access: Public
Created: Mar 12, 2024
Updated: Mar 12, 2024
SHA: 9155be2d

Base models

google/vit-base-patch16-224-in21k

Model card

From the Hugging Face model README

test-hasy-6

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the HASY dataset. It achieves the following results on the evaluation set:

Loss: 0.6506
Accuracy: 0.8025

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1787
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.0857	1.0	541	2.4484	0.5572
2.3006	2.0	1082	2.1588	0.5904
2.4406	3.0	1623	1.8879	0.6445
2.342	4.0	2164	1.7122	0.6674
2.1852	5.0	2705	1.5467	0.6923
1.9535	6.0	3246	1.4113	0.7048
1.9061	7.0	3787	1.3136	0.6881
1.5934	8.0	4328	1.2059	0.7089
1.8755	9.0	4869	1.1638	0.7173
1.6319	10.0	5410	1.1024	0.7235
1.5899	11.0	5951	1.0375	0.7339
1.6427	12.0	6492	0.9656	0.7526
1.8022	13.0	7033	0.9760	0.7422
1.7161	14.0	7574	0.8952	0.7609
1.2123	15.0	8115	0.8750	0.7692
1.5721	16.0	8656	0.8586	0.7755
1.7482	17.0	9197	0.8279	0.7755
1.5992	18.0	9738	0.8321	0.7547
1.8179	19.0	10279	0.7898	0.7817
1.2744	20.0	10820	0.7984	0.7672
1.2221	21.0	11361	0.7757	0.7734
1.4893	22.0	11902	0.7512	0.7817
1.5184	23.0	12443	0.7512	0.7817
1.6562	24.0	12984	0.7514	0.7796
1.4148	25.0	13525	0.7241	0.7817
1.2765	26.0	14066	0.6907	0.8046
1.3378	27.0	14607	0.7132	0.7900
1.5446	28.0	15148	0.6973	0.7963
1.1969	29.0	15689	0.7010	0.7921
1.3721	30.0	16230	0.6928	0.8004
1.4051	31.0	16771	0.6976	0.7921
1.1004	32.0	17312	0.6785	0.8004
1.2668	33.0	17853	0.6883	0.7817
1.0728	34.0	18394	0.6924	0.7859
1.1856	35.0	18935	0.6840	0.7921
1.2387	36.0	19476	0.6739	0.8025
1.5242	37.0	20017	0.6554	0.7963
1.351	38.0	20558	0.6736	0.7942
1.2441	39.0	21099	0.6659	0.8046
1.2113	40.0	21640	0.6709	0.7983
1.1608	41.0	22181	0.6630	0.7983
1.266	42.0	22722	0.6693	0.8004
0.9426	43.0	23263	0.6639	0.8046
1.0066	44.0	23804	0.6636	0.8025
1.0856	45.0	24345	0.6530	0.8004
1.0128	46.0	24886	0.6506	0.8025
1.0369	47.0	25427	0.6617	0.8025
1.1458	48.0	25968	0.6546	0.8004
1.0696	49.0	26509	0.6597	0.7942
1.2227	50.0	27050	0.6566	0.7942

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Mar 12, 2024
Updated: Mar 12, 2024