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Augusto777/
swinv2-tiny-patch4-window8-256-DMAE-15e-6

Name: swinv2-tiny-patch4-window8-256-DMAE-15e-6
Availability: InStock

tensorboard

safetensors

swinv2

generated_from_trainer

imagefolder

microsoft/swinv2-tiny-patch4-window8-256

finetune

apache-2.0

model-index

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swinv2-tiny-patch4-window8-256-DMAE-15e-6

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

Loss: 7.9433
Accuracy: 0.1087

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: 1.5e-06
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: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.86	3	7.9433	0.1087
No log	2.0	7	7.9425	0.1087
7.9661	2.86	10	7.9414	0.1087
7.9661	4.0	14	7.9392	0.1087
7.9661	4.86	17	7.9372	0.1087
7.9068	6.0	21	7.9343	0.1087
7.9068	6.86	24	7.9320	0.1087
7.9068	8.0	28	7.9288	0.1087
7.7849	8.86	31	7.9262	0.1087
7.7849	10.0	35	7.9226	0.1087
7.7849	10.86	38	7.9198	0.1087
8.0613	12.0	42	7.9159	0.1087
8.0613	12.86	45	7.9129	0.1087
8.0613	14.0	49	7.9088	0.1087
7.827	14.86	52	7.9057	0.1087
7.827	16.0	56	7.9015	0.1087
7.827	16.86	59	7.8984	0.1087
7.8359	18.0	63	7.8942	0.1087
7.8359	18.86	66	7.8910	0.1087
7.9032	20.0	70	7.8869	0.1087
7.9032	20.86	73	7.8839	0.1087
7.9032	22.0	77	7.8799	0.1087
7.9294	22.86	80	7.8771	0.1087
7.9294	24.0	84	7.8735	0.1087
7.9294	24.86	87	7.8710	0.1087
7.9185	26.0	91	7.8679	0.1087
7.9185	26.86	94	7.8659	0.1087
7.9185	28.0	98	7.8634	0.1087
7.7948	28.86	101	7.8618	0.1087
7.7948	30.0	105	7.8600	0.1087
7.7948	30.86	108	7.8589	0.1087
7.906	32.0	112	7.8578	0.1087
7.906	32.86	115	7.8573	0.1087
7.906	34.0	119	7.8569	0.1087
7.9031	34.29	120	7.8569	0.1087

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu118
Datasets 2.16.1
Tokenizers 0.15.0

Augusto777/swinv2-tiny-patch4-window8-256-DMAE-15e-6

swinv2-tiny-patch4-window8-256-DMAE-15e-6

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Augusto777/
swinv2-tiny-patch4-window8-256-DMAE-15e-6