klasifikasiburung – AI Model by riyadifirman | AlphaNeural AI

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riyadifirman/
klasifikasiburung

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image-classification

generated_from_trainer

RobertZ2011/resnet-18-birb

autotrain_compatible

endpoints_compatible

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klasifikasiburung

This model is a fine-tuned version of RobertZ2011/resnet-18-birb on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0186
Accuracy: 0.7565
Precision: 0.7631
Recall: 0.7565
F1: 0.7554

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.5955	1.0	188	1.4442	0.7235	0.7426	0.7235	0.7169
1.1224	2.0	376	1.2881	0.7458	0.7546	0.7458	0.7406
0.7778	3.0	564	1.1965	0.7501	0.7635	0.7501	0.7483
0.5573	4.0	752	1.1417	0.7565	0.7635	0.7565	0.7538
0.4231	5.0	940	1.1077	0.7584	0.7671	0.7584	0.7567
0.2878	6.0	1128	1.0893	0.7601	0.7716	0.7601	0.7597
0.2043	7.0	1316	1.0688	0.7591	0.7661	0.7591	0.7579
0.1326	8.0	1504	1.0687	0.7582	0.7653	0.7582	0.7565
0.0851	9.0	1692	1.0502	0.7598	0.7652	0.7598	0.7581
0.0807	10.0	1880	1.0318	0.7582	0.7644	0.7582	0.7569
0.0581	11.0	2068	1.0403	0.7572	0.7629	0.7572	0.7558
0.043	12.0	2256	1.0295	0.7565	0.7633	0.7565	0.7557
0.0379	13.0	2444	1.0271	0.7568	0.7636	0.7568	0.7557
0.0399	14.0	2632	1.0319	0.7558	0.7627	0.7558	0.7549
0.0447	15.0	2820	1.0186	0.7565	0.7631	0.7565	0.7554

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1