vit-base-patch16-384-finetuned-galaxy10-decals

matthieulel/vit-base-patch16-384-finetuned-galaxy10-decals

vit-base-patch16-384-finetuned-galaxy10-decals is a image classification model from matthieulel. 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: vit
Access: Public
Created: Jun 10, 2024
Updated: Jun 10, 2024
SHA: d6753895

Base models

google/vit-base-patch16-384

Model card

From the Hugging Face model README

vit-base-patch16-384-finetuned-galaxy10-decals

This model is a fine-tuned version of google/vit-base-patch16-384 on the matthieulel/galaxy10_decals dataset. It achieves the following results on the evaluation set:

Loss: 0.5422
Accuracy: 0.8613
Precision: 0.8600
Recall: 0.8613
F1: 0.8596

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: 0.0001
train_batch_size: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
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	Precision	Recall	F1
1.5894	0.99	31	1.2732	0.5744	0.5409	0.5744	0.5481
0.8001	1.98	62	0.6184	0.7976	0.7934	0.7976	0.7880
0.6895	2.98	93	0.5823	0.8067	0.7991	0.8067	0.7955
0.6259	4.0	125	0.4910	0.8433	0.8427	0.8433	0.8368
0.556	4.99	156	0.4874	0.8467	0.8465	0.8467	0.8465
0.5116	5.98	187	0.4734	0.8546	0.8569	0.8546	0.8518
0.4877	6.98	218	0.4539	0.8461	0.8429	0.8461	0.8428
0.4383	8.0	250	0.4716	0.8377	0.8399	0.8377	0.8345
0.4267	8.99	281	0.4355	0.8602	0.8576	0.8602	0.8559
0.4022	9.98	312	0.4758	0.8377	0.8377	0.8377	0.8356
0.3811	10.98	343	0.4538	0.8495	0.8471	0.8495	0.8474
0.3612	12.0	375	0.4808	0.8439	0.8412	0.8439	0.8399
0.363	12.99	406	0.4751	0.8467	0.8502	0.8467	0.8458
0.3198	13.98	437	0.4800	0.8489	0.8497	0.8489	0.8450
0.3192	14.98	468	0.4834	0.8574	0.8580	0.8574	0.8570
0.3041	16.0	500	0.4879	0.8495	0.8500	0.8495	0.8443
0.2607	16.99	531	0.4958	0.8540	0.8529	0.8540	0.8523
0.2649	17.98	562	0.4927	0.8579	0.8570	0.8579	0.8562
0.2553	18.98	593	0.5095	0.8495	0.8473	0.8495	0.8474
0.2453	20.0	625	0.5162	0.8495	0.8467	0.8495	0.8467
0.2417	20.99	656	0.5375	0.8579	0.8573	0.8579	0.8543
0.241	21.98	687	0.5129	0.8568	0.8546	0.8568	0.8547
0.2257	22.98	718	0.5316	0.8596	0.8584	0.8596	0.8571
0.2087	24.0	750	0.5530	0.8512	0.8497	0.8512	0.8489
0.2196	24.99	781	0.5422	0.8613	0.8600	0.8613	0.8596
0.1975	25.98	812	0.5672	0.8529	0.8534	0.8529	0.8508
0.2135	26.98	843	0.5697	0.8523	0.8513	0.8523	0.8509
0.1946	28.0	875	0.5598	0.8557	0.8542	0.8557	0.8536
0.2006	28.99	906	0.5582	0.8591	0.8566	0.8591	0.8560
0.1968	29.76	930	0.5571	0.8591	0.8571	0.8591	0.8564

Framework versions

Transformers 4.37.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.15.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jun 10, 2024
Updated: Jun 10, 2024