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Augusto777/
BEiT-DMAE-13XDA-REVAL-80-32

Name: BEiT-DMAE-13XDA-REVAL-80-32
Availability: InStock

tensorboard

safetensors

beit

generated_from_trainer

imagefolder

microsoft/beit-base-patch16-224

finetune

apache-2.0

model-index

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BEiT-DMAE-13XDA-REVAL-80-32

This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.8105
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: 3.5e-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: 80

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.5474	1.0	60	1.2945	0.4565
1.3959	1.99	120	1.2745	0.4565
1.0517	2.99	180	0.9632	0.6087
0.7273	4.0	241	0.7709	0.6957
0.5246	5.0	301	0.7217	0.7391
0.3645	5.99	361	0.7142	0.8043
0.2211	6.99	421	0.6436	0.8043
0.266	8.0	482	1.1316	0.6087
0.1235	9.0	542	0.9257	0.7826
0.1613	9.99	602	0.8527	0.7826
0.0946	10.99	662	0.8274	0.8043
0.1392	12.0	723	0.8312	0.7609
0.1028	13.0	783	1.1959	0.7609
0.1072	13.99	843	1.0017	0.7391
0.0888	14.99	903	0.9214	0.8043
0.0951	16.0	964	0.9156	0.7609
0.0714	17.0	1024	1.3116	0.6957
0.0804	17.99	1084	1.1107	0.7826
0.08	18.99	1144	0.8105	0.8478
0.1619	20.0	1205	0.7581	0.8261
0.084	21.0	1265	1.0210	0.8261
0.072	21.99	1325	1.3092	0.7609
0.0303	22.99	1385	1.3367	0.7826
0.0228	24.0	1446	1.0277	0.8261
0.0755	25.0	1506	0.9436	0.8261
0.0756	25.99	1566	1.1588	0.7609
0.0875	26.99	1626	1.3280	0.7174
0.0771	28.0	1687	1.8558	0.6739
0.0467	29.0	1747	1.6476	0.7391
0.0382	29.99	1807	0.9374	0.8478
0.0511	30.99	1867	1.0847	0.8043
0.0161	32.0	1928	1.2028	0.7826
0.0301	33.0	1988	1.2971	0.7391
0.0443	33.99	2048	1.3993	0.7174
0.0782	34.99	2108	1.3359	0.8043
0.0287	36.0	2169	1.3011	0.7826
0.0347	37.0	2229	1.2450	0.7826
0.0538	37.99	2289	1.8216	0.7609
0.027	38.99	2349	1.1701	0.8043
0.038	40.0	2410	1.1025	0.8043
0.0244	41.0	2470	1.2912	0.7609
0.0122	41.99	2530	1.5699	0.7609
0.023	42.99	2590	1.5114	0.7826
0.0297	44.0	2651	1.2189	0.8478
0.0284	45.0	2711	1.3997	0.7826
0.0203	45.99	2771	1.4792	0.8043
0.03	46.99	2831	1.7487	0.7174
0.025	48.0	2892	1.6605	0.7609
0.0134	49.0	2952	1.4106	0.7826
0.026	49.99	3012	1.2972	0.7609
0.0507	50.99	3072	1.3303	0.7826
0.0394	52.0	3133	1.1954	0.8478
0.0271	53.0	3193	1.3125	0.8261
0.0115	53.99	3253	1.3444	0.8478
0.0138	54.99	3313	1.4689	0.8261
0.0184	56.0	3374	1.4959	0.8261
0.0163	57.0	3434	1.3490	0.7826
0.0112	57.99	3494	1.4749	0.7826
0.0185	58.99	3554	1.5823	0.7826
0.031	60.0	3615	1.5190	0.7826
0.0161	61.0	3675	1.5476	0.8043
0.0146	61.99	3735	1.3930	0.7826
0.005	62.99	3795	1.5454	0.8043
0.0093	64.0	3856	1.5959	0.7826
0.0224	65.0	3916	1.4554	0.8043
0.0154	65.99	3976	1.5327	0.8261
0.0116	66.99	4036	1.6030	0.8043
0.0037	68.0	4097	1.5046	0.8261
0.0023	69.0	4157	1.5222	0.8261
0.0068	69.99	4217	1.4339	0.8261
0.0342	70.99	4277	1.6964	0.8043
0.0077	72.0	4338	1.6102	0.8043
0.0043	73.0	4398	1.6687	0.8043
0.0131	73.99	4458	1.6847	0.8043
0.0031	74.99	4518	1.7195	0.8043
0.0087	76.0	4579	1.7209	0.7826
0.0219	77.0	4639	1.6715	0.8043
0.0229	77.99	4699	1.6823	0.8043
0.008	78.99	4759	1.6751	0.8043
0.0051	79.67	4800	1.6758	0.8043

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu118
Datasets 2.16.1
Tokenizers 0.15.0

Augusto777/BEiT-DMAE-13XDA-REVAL-80-32

BEiT-DMAE-13XDA-REVAL-80-32

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Augusto777/
BEiT-DMAE-13XDA-REVAL-80-32