dinov2-base-finetuned-galaxy10-decals

matthieulel/dinov2-base-finetuned-galaxy10-decals

dinov2-base-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: dinov2
Access: Public
Created: Apr 26, 2024
Updated: Jun 11, 2024
SHA: c5fcfcbc

Base models

facebook/dinov2-base

Model card

From the Hugging Face model README

dinov2-base-finetuned-galaxy10-decals

This model is a fine-tuned version of facebook/dinov2-base on the matthieulel/galaxy10_decals dataset. It achieves the following results on the evaluation set:

Loss: 0.5538
Accuracy: 0.8630
Precision: 0.8630
Recall: 0.8630
F1: 0.8607

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: 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
1.1698	0.99	31	0.9105	0.6635	0.6861	0.6635	0.6488
0.7528	1.98	62	0.6494	0.7790	0.8147	0.7790	0.7613
0.6893	2.98	93	0.6538	0.7943	0.8020	0.7943	0.7912
0.6554	4.0	125	0.6333	0.7886	0.8071	0.7886	0.7773
0.6342	4.99	156	0.5532	0.8134	0.8198	0.8134	0.8138
0.5565	5.98	187	0.5324	0.8207	0.8343	0.8207	0.8180
0.5475	6.98	218	0.5030	0.8354	0.8387	0.8354	0.8343
0.5271	8.0	250	0.4834	0.8337	0.8444	0.8337	0.8325
0.5086	8.99	281	0.4611	0.8433	0.8441	0.8433	0.8382
0.4341	9.98	312	0.4437	0.8506	0.8539	0.8506	0.8509
0.4557	10.98	343	0.4559	0.8484	0.8529	0.8484	0.8495
0.4179	12.0	375	0.5942	0.8129	0.8257	0.8129	0.8133
0.4243	12.99	406	0.4599	0.8540	0.8537	0.8540	0.8518
0.372	13.98	437	0.4743	0.8410	0.8472	0.8410	0.8403
0.4003	14.98	468	0.4749	0.8478	0.8471	0.8478	0.8461
0.344	16.0	500	0.4678	0.8596	0.8575	0.8596	0.8572
0.3252	16.99	531	0.5024	0.8472	0.8470	0.8472	0.8459
0.3166	17.98	562	0.5038	0.8439	0.8442	0.8439	0.8418
0.2978	18.98	593	0.5240	0.8365	0.8351	0.8365	0.8349
0.2748	20.0	625	0.5176	0.8512	0.8497	0.8512	0.8472
0.2691	20.99	656	0.5529	0.8534	0.8514	0.8534	0.8506
0.2571	21.98	687	0.5441	0.8563	0.8573	0.8563	0.8535
0.2451	22.98	718	0.5440	0.8427	0.8427	0.8427	0.8412
0.2256	24.0	750	0.5489	0.8506	0.8467	0.8506	0.8474
0.2304	24.99	781	0.5695	0.8534	0.8492	0.8534	0.8498
0.2102	25.98	812	0.5347	0.8568	0.8533	0.8568	0.8540
0.2172	26.98	843	0.5399	0.8523	0.8525	0.8523	0.8518
0.1953	28.0	875	0.5699	0.8551	0.8547	0.8551	0.8522
0.2035	28.99	906	0.5538	0.8630	0.8630	0.8630	0.8607
0.1926	29.76	930	0.5435	0.8630	0.8609	0.8630	0.8606

Framework versions

Transformers 4.37.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.15.1

Task: Image Classification
Library: transformers
Type: dinov2
License: apache-2.0
Created: Apr 26, 2024
Updated: Jun 11, 2024