swinv2-tiny-patch4-window8-256-finetuned-eurosat – AI Model by lu5 | AlphaNeural AI

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lu5/
swinv2-tiny-patch4-window8-256-finetuned-eurosat

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image-classification

generated_from_trainer

microsoft/swinv2-tiny-patch4-window8-256

autotrain_compatible

endpoints_compatible

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swinv2-tiny-patch4-window8-256-finetuned-eurosat

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the food101 dataset. It achieves the following results on the evaluation set:

Loss: 0.3997
Accuracy: 0.8859

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8552	1.0	592	1.1245	0.6955
1.2938	2.0	1184	0.6712	0.8131
1.2294	3.0	1776	0.5354	0.8492
1.0199	4.0	2368	0.4958	0.8594
0.9914	5.0	2960	0.4633	0.8678
0.8786	6.0	3552	0.4390	0.8750
0.806	7.0	4144	0.4206	0.8791
0.7506	8.0	4736	0.4093	0.8832
0.7433	9.0	5328	0.4053	0.8841
0.6393	10.0	5920	0.3997	0.8859

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3