This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.1349
Accuracy: 0.9476

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2131	1.0	51	0.1843	0.9320
0.1521	2.0	102	0.1215	0.9552
0.1318	3.0	153	0.1349	0.9476

Framework versions

Transformers 4.37.2
Pytorch 1.13.1
Datasets 2.16.1
Tokenizers 0.15.1

friedrice231/MemeDetector_SG

swin-tiny-patch4-window7-224-finetuned-eurosat

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

friedrice231/
MemeDetector_SG