swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-galaxy10-decals

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the matthieulel/galaxy10_decals dataset. It achieves the following results on the evaluation set:

• Loss: 0.5226
• Accuracy: 0.8591
• Precision: 0.8571
• Recall: 0.8591
• F1: 0.8567

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• 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
1.0846	0.99	62	0.8092	0.7272	0.7246	0.7272	0.7101
0.7867	2.0	125	0.6366	0.7988	0.7996	0.7988	0.7895
0.6835	2.99	187	0.5315	0.8207	0.8195	0.8207	0.8157
0.586	4.0	250	0.4611	0.8489	0.8468	0.8489	0.8452
0.5263	4.99	312	0.4753	0.8399	0.8421	0.8399	0.8400
0.5341	6.0	375	0.4551	0.8427	0.8433	0.8427	0.8386
0.4743	6.99	437	0.4639	0.8382	0.8433	0.8382	0.8391
0.4573	8.0	500	0.4771	0.8360	0.8422	0.8360	0.8345
0.4368	8.99	562	0.4731	0.8472	0.8450	0.8472	0.8452
0.4022	10.0	625	0.4736	0.8540	0.8528	0.8540	0.8516
0.4005	10.99	687	0.4542	0.8551	0.8554	0.8551	0.8547
0.3514	12.0	750	0.5543	0.8467	0.8527	0.8467	0.8471
0.3565	12.99	812	0.5318	0.8506	0.8535	0.8506	0.8493
0.3717	14.0	875	0.5059	0.8579	0.8582	0.8579	0.8574
0.3343	14.99	937	0.5235	0.8472	0.8492	0.8472	0.8474
0.3053	16.0	1000	0.5226	0.8591	0.8571	0.8591	0.8567
0.2607	16.99	1062	0.5654	0.8591	0.8579	0.8591	0.8572
0.2814	18.0	1125	0.5622	0.8546	0.8541	0.8546	0.8537
0.2735	18.99	1187	0.6185	0.8506	0.8525	0.8506	0.8508
0.2673	20.0	1250	0.6210	0.8574	0.8544	0.8574	0.8550
0.2595	20.99	1312	0.6334	0.8422	0.8415	0.8422	0.8399
0.2583	22.0	1375	0.6565	0.8540	0.8545	0.8540	0.8527
0.239	22.99	1437	0.6859	0.8455	0.8458	0.8455	0.8447
0.2174	24.0	1500	0.6709	0.8591	0.8581	0.8591	0.8581
0.2288	24.99	1562	0.7437	0.8444	0.8426	0.8444	0.8419
0.2305	26.0	1625	0.7048	0.8529	0.8497	0.8529	0.8505
0.2071	26.99	1687	0.7152	0.8540	0.8527	0.8540	0.8529
0.2282	28.0	1750	0.7273	0.8568	0.8559	0.8568	0.8554
0.209	28.99	1812	0.7213	0.8557	0.8534	0.8557	0.8540
0.2078	29.76	1860	0.7273	0.8563	0.8544	0.8563	0.8548

Framework versions

• Transformers 4.37.2
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.15.1