meat_calssify_fresh_crop_fixed_V_0_3

talli96123/meat_calssify_fresh_crop_fixed_V_0_3

meat_calssify_fresh_crop_fixed_V_0_3 is a image classification model from talli96123. 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: Jun 11, 2024
Updated: Jun 11, 2024
SHA: e0723322

Base models

google/vit-base-patch16-224-in21k

Datasets

imagefolder

Model card

From the Hugging Face model README

meat_calssify_fresh_crop_fixed_V_0_3

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

Loss: 1.6191
Accuracy: 0.75

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: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0921	1.0	621	1.0844	0.3654
1.0438	2.0	1242	1.1755	0.4423
1.1558	3.0	1863	1.0148	0.4487
1.1274	4.0	2484	1.0371	0.5705
1.1992	5.0	3105	1.0598	0.3718
1.2195	6.0	3726	1.3422	0.5256
1.2366	7.0	4347	1.8744	0.4359
1.1302	8.0	4968	1.4699	0.5705
1.1137	9.0	5589	1.3480	0.6154
0.9534	10.0	6210	1.4723	0.5769
1.0269	11.0	6831	1.0999	0.6538
1.0545	12.0	7452	1.2980	0.6090
0.8669	13.0	8073	1.3408	0.6731
0.9571	14.0	8694	1.4879	0.6474
0.8345	15.0	9315	1.4030	0.6603
0.6623	16.0	9936	1.0840	0.7308
0.6014	17.0	10557	1.5054	0.7115
0.5599	18.0	11178	1.1956	0.7628
0.7209	19.0	11799	1.9734	0.5962
0.6289	20.0	12420	1.6165	0.6923
0.429	21.0	13041	1.5766	0.6987
0.628	22.0	13662	1.3948	0.7179
0.5427	23.0	14283	1.7663	0.6795
0.3806	24.0	14904	1.6219	0.6987
0.4443	25.0	15525	1.5065	0.7051
0.3648	26.0	16146	1.5225	0.7308
0.3812	27.0	16767	1.3488	0.75
0.3106	28.0	17388	1.7758	0.6987
0.3725	29.0	18009	1.4190	0.7372
0.4284	30.0	18630	1.6205	0.7115
0.2257	31.0	19251	1.5535	0.7628
0.2869	32.0	19872	1.2077	0.8013
0.3128	33.0	20493	1.9065	0.7051
0.2802	34.0	21114	1.2794	0.7885
0.2647	35.0	21735	1.5823	0.7436
0.3054	36.0	22356	1.3412	0.7756
0.2619	37.0	22977	1.4471	0.7308
0.2289	38.0	23598	1.8176	0.7244
0.1554	39.0	24219	1.5014	0.7628
0.1794	40.0	24840	1.4112	0.7628
0.1835	41.0	25461	1.8688	0.7244
0.2177	42.0	26082	1.2748	0.7821
0.1063	43.0	26703	1.4471	0.7628
0.1798	44.0	27324	1.1872	0.7949
0.1511	45.0	27945	1.3028	0.8077
0.1659	46.0	28566	1.7257	0.7308
0.0917	47.0	29187	1.2314	0.8205
0.1554	48.0	29808	1.4090	0.7821
0.0927	49.0	30429	1.0295	0.8397
0.1188	50.0	31050	1.6191	0.75

Framework versions

Transformers 4.41.2
Pytorch 2.3.0
Datasets 2.19.2
Tokenizers 0.19.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jun 11, 2024
Updated: Jun 11, 2024