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: 2.7347
F1: 0.0

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
0.0296	1.0	105	3.2075
0.0377	2.0	210	2.6132
0.0104	3.0	315	2.2246
0.0177	4.0	420	2.6363
0.007	5.0	525	2.6364
0.0082	6.0	630	2.6554
0.0078	7.0	735	2.6351
0.0015	8.0	840	2.6925
0.0073	9.0	945	2.7134
0.0018	10.0	1050	2.7347

Framework versions

Transformers 4.34.1
Pytorch 1.12.1
Datasets 2.14.5
Tokenizers 0.14.1

Mahendra42/swin-tiny-patch4-window7-224_RCC_Classifierv4

swin-tiny-patch4-window7-224_RCC_Classifierv4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mahendra42/
swin-tiny-patch4-window7-224_RCC_Classifierv4