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Augusto777/
SW2-DMAE

Name: SW2-DMAE
Rating: 2.5 (5 reviews)

tensorboard

safetensors

swinv2

generated_from_trainer

imagefolder

microsoft/swinv2-tiny-patch4-window8-256

finetune

apache-2.0

model-index

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SW2-DMAE

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: 1.6739
Accuracy: 0.4565

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: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.86	3	7.9394	0.1087
No log	2.0	7	7.8979	0.1087
7.935	2.86	10	7.7672	0.1087
7.935	4.0	14	7.2197	0.1087
7.935	4.86	17	6.5661	0.1087
7.0143	6.0	21	5.7304	0.1087
7.0143	6.86	24	5.1184	0.1087
7.0143	8.0	28	4.3526	0.1087
4.9972	8.86	31	3.8117	0.1087
4.9972	10.0	35	3.1518	0.1087
4.9972	10.86	38	2.7125	0.1087
3.3803	12.0	42	2.2254	0.1087
3.3803	12.86	45	1.9450	0.1087
3.3803	14.0	49	1.6739	0.4565
2.0759	14.86	52	1.5299	0.4565
2.0759	16.0	56	1.3876	0.4565
2.0759	16.86	59	1.3059	0.4565
1.4466	18.0	63	1.2341	0.4565
1.4466	18.86	66	1.2120	0.4565
1.2349	20.0	70	1.2096	0.4565
1.2349	20.86	73	1.2118	0.4565
1.2349	22.0	77	1.2114	0.4565
1.1854	22.86	80	1.2141	0.4565
1.1854	24.0	84	1.2117	0.4565
1.1854	24.86	87	1.2102	0.4565
1.1878	26.0	91	1.2076	0.4565
1.1878	26.86	94	1.2083	0.4565
1.1878	28.0	98	1.2130	0.4565
1.1986	28.86	101	1.2069	0.4565
1.1986	30.0	105	1.2058	0.4565
1.1986	30.86	108	1.2070	0.4565
1.182	32.0	112	1.2075	0.4565
1.182	32.86	115	1.2074	0.4565
1.182	34.0	119	1.2072	0.4565
1.2064	34.29	120	1.2072	0.4565

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu118
Datasets 2.16.1
Tokenizers 0.15.0

Augusto777/SW2-DMAE

SW2-DMAE

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Augusto777/
SW2-DMAE