beit-base-patch16-224-pt22k-ft22k-rim_one-new

SiddharthaM/beit-base-patch16-224-pt22k-ft22k-rim_one-new

beit-base-patch16-224-pt22k-ft22k-rim_one-new is a image classification model from SiddharthaM. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: beit
Access: Public
Created: Jul 6, 2022
Updated: Jul 6, 2022
SHA: 1dbf3c79

Datasets

imagefolder

Model card

From the Hugging Face model README

beit-base-patch16-224-pt22k-ft22k-rim_one-new

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.4550
Accuracy: 0.8767

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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.73	2	0.2411	0.9178
No log	1.73	4	0.2182	0.8973
No log	2.73	6	0.3085	0.8973
No log	3.73	8	0.2794	0.8973
0.1392	4.73	10	0.2398	0.9110
0.1392	5.73	12	0.2925	0.8973
0.1392	6.73	14	0.2798	0.9110
0.1392	7.73	16	0.2184	0.9178
0.1392	8.73	18	0.3007	0.9110
0.0416	9.73	20	0.3344	0.9041
0.0416	10.73	22	0.3626	0.9110
0.0416	11.73	24	0.4842	0.8904
0.0416	12.73	26	0.3664	0.8973
0.0416	13.73	28	0.3458	0.9110
0.0263	14.73	30	0.2810	0.9110
0.0263	15.73	32	0.4695	0.8699
0.0263	16.73	34	0.3723	0.9041
0.0263	17.73	36	0.3447	0.9041
0.0263	18.73	38	0.3708	0.8904
0.0264	19.73	40	0.4052	0.9110
0.0264	20.73	42	0.4492	0.9041
0.0264	21.73	44	0.4649	0.8904
0.0264	22.73	46	0.4061	0.9178
0.0264	23.73	48	0.4136	0.9110
0.0139	24.73	50	0.4183	0.8973
0.0139	25.73	52	0.4504	0.8904
0.0139	26.73	54	0.4368	0.8973
0.0139	27.73	56	0.4711	0.9110
0.0139	28.73	58	0.3928	0.9110
0.005	29.73	60	0.4550	0.8767

Framework versions

Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1

Task: Image Classification
Library: transformers
Type: beit
License: apache-2.0
Created: Jul 6, 2022
Updated: Jul 6, 2022