beit-base-patch16-224-DMAE-5e-5

Augusto777/beit-base-patch16-224-DMAE-5e-5

beit-base-patch16-224-DMAE-5e-5 is a machine learning model from Augusto777. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

23% of all-time downloads

All-time downloads

Public

Parameters

85.8M

343 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors343 MB · 100%

At a glance

License: apache-2.0
Model type: beit
Access: Public
Created: Dec 1, 2024
Updated: Dec 1, 2024
SHA: c30d14c7

Base models

microsoft/beit-base-patch16-224

Datasets

imagefolder

Model card

From the Hugging Face model README

beit-base-patch16-224-DMAE-5e-5

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: 0.6236
Accuracy: 0.8043

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	1.3816	0.4565
No log	2.0	7	1.3504	0.4565
1.3654	2.86	10	1.3075	0.4565
1.3654	4.0	14	1.2444	0.4565
1.3654	4.86	17	1.2089	0.4565
1.2386	6.0	21	1.1711	0.4565
1.2386	6.86	24	1.1492	0.4565
1.2386	8.0	28	1.1050	0.4783
1.132	8.86	31	1.0928	0.6522
1.132	10.0	35	1.0230	0.6739
1.132	10.86	38	0.9864	0.6522
1.015	12.0	42	1.0060	0.6739
1.015	12.86	45	0.8790	0.7174
1.015	14.0	49	0.8533	0.6739
0.9217	14.86	52	0.8203	0.6957
0.9217	16.0	56	0.8152	0.6739
0.9217	16.86	59	0.8598	0.6522
0.7989	18.0	63	0.7979	0.6957
0.7989	18.86	66	0.7555	0.6739
0.7309	20.0	70	0.7019	0.7609
0.7309	20.86	73	0.7254	0.7174
0.7309	22.0	77	0.7268	0.6739
0.6267	22.86	80	0.7096	0.6739
0.6267	24.0	84	0.7568	0.6739
0.6267	24.86	87	0.6565	0.7391
0.564	26.0	91	0.7035	0.7391
0.564	26.86	94	0.7081	0.7391
0.564	28.0	98	0.6236	0.8043
0.5625	28.86	101	0.6091	0.8043
0.5625	30.0	105	0.6523	0.7609
0.5625	30.86	108	0.6235	0.7826
0.5185	32.0	112	0.5974	0.7826
0.5185	32.86	115	0.5944	0.7826
0.5185	34.0	119	0.6005	0.7826
0.5005	34.29	120	0.6005	0.7826

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu118
Datasets 2.16.1
Tokenizers 0.15.0

Type: beit
License: apache-2.0
Created: Dec 1, 2024
Updated: Dec 1, 2024