This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3526
Accuracy: 0.8226
Precision: 0.9245
Recall: 0.875
F1: 0.5829
Auc: 0.6042

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	Precision	Recall	F1	Auc
No log	1.0	7	0.3296	0.9032	0.9032	1.0	0.4746	0.5
0.4795	2.0	14	0.3129	0.9032	0.9032	1.0	0.4746	0.5
0.2503	3.0	21	0.3182	0.9032	0.9032	1.0	0.4746	0.5
0.2503	4.0	28	0.2973	0.9032	0.9032	1.0	0.4746	0.5
0.2231	5.0	35	0.3275	0.9032	0.9032	1.0	0.4746	0.5
0.1791	6.0	42	0.3147	0.9032	0.9032	1.0	0.4746	0.5
0.1791	7.0	49	0.3401	0.8978	0.9071	0.9881	0.5206	0.5218
0.1361	8.0	56	0.3885	0.7849	0.9211	0.8333	0.5529	0.5833
0.1245	9.0	63	0.3192	0.8817	0.9195	0.9524	0.6012	0.5873
0.0902	10.0	70	0.3526	0.8226	0.9245	0.875	0.5829	0.6042

Framework versions

Transformers 4.41.1
Pytorch 2.0.0+cu117
Datasets 2.19.1
Tokenizers 0.19.1

synergyai-jaeung/swin-tiny-patch4-window7-224-finetuned-RCC

swin-tiny-patch4-window7-224-finetuned-RCC

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

synergyai-jaeung/
swin-tiny-patch4-window7-224-finetuned-RCC