vit-base-patch16-224-finetuned-algae-rgb – AI Model by samitizerxu | AlphaNeural AI

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samitizerxu/
vit-base-patch16-224-finetuned-algae-rgb

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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vit-base-patch16-224-finetuned-algae-rgb

This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0685
Accuracy: 0.6174

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
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.981	1.0	120	1.0513	0.5698
1.0027	2.0	240	1.0316	0.5775
0.9554	3.0	360	0.9944	0.5945
0.978	4.0	480	0.9735	0.5980
0.8983	5.0	600	0.9690	0.6033
0.8561	6.0	720	0.9714	0.5968
0.8438	7.0	840	0.9833	0.6039
0.808	8.0	960	0.9827	0.6138
0.7882	9.0	1080	0.9971	0.5962
0.7422	10.0	1200	0.9901	0.6080
0.7797	11.0	1320	1.0096	0.5921
0.7167	12.0	1440	1.0252	0.6092
0.7445	13.0	1560	1.0364	0.6074
0.6641	14.0	1680	1.0471	0.6092
0.6847	15.0	1800	1.0693	0.6138
0.6418	16.0	1920	1.0685	0.6174
0.6423	17.0	2040	1.0683	0.6127
0.6432	18.0	2160	1.0729	0.6127
0.6208	19.0	2280	1.0801	0.6138
0.588	20.0	2400	1.0802	0.6103

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2