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