swin-base-patch4-window7-224-20epochs-finetuned-memes

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: 0.7090
• Accuracy: 0.8478

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: 0.00012
• 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
1.0238	0.99	40	0.9636	0.6445
0.777	1.99	80	0.6591	0.7666
0.4763	2.99	120	0.5381	0.8130
0.3215	3.99	160	0.5244	0.8253
0.2179	4.99	200	0.5123	0.8238
0.1868	5.99	240	0.5052	0.8308
0.154	6.99	280	0.5444	0.8338
0.1166	7.99	320	0.6318	0.8238
0.1099	8.99	360	0.5656	0.8338
0.0925	9.99	400	0.6057	0.8338
0.0779	10.99	440	0.5942	0.8393
0.0629	11.99	480	0.6112	0.8400
0.0742	12.99	520	0.6588	0.8331
0.0752	13.99	560	0.6143	0.8408
0.0577	14.99	600	0.6450	0.8516
0.0589	15.99	640	0.6787	0.8400
0.0555	16.99	680	0.6641	0.8454
0.052	17.99	720	0.7213	0.8524
0.0589	18.99	760	0.6917	0.8470
0.0506	19.99	800	0.7090	0.8478

Framework versions

• Transformers 4.22.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1