dino-vits16-val08483-vit-tuned-sota

pcam-interpretability/dino-vits16-val08483-vit-tuned-sota

dino-vits16-val08483-vit-tuned-sota is a machine learning model from pcam-interpretability. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

Downloads · 30 days

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Public

Updated Apr 29, 2025

Repo size

86.8 MB

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Public

Hugging Face

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.pth86.8 MB · 100%

At a glance

Access: Public
Created: Apr 29, 2025
Updated: Apr 29, 2025
SHA: f393522b

Model card

From the Hugging Face model README

dino-vits16

Best Validation Accuracy: 0.8483

Metadata

Model Name: dino-vits16
Optimizer: adamw
Scheduler: cosine
Weight Decay: 0.001
Warmup Epochs: 10
Patience: 10
Amp: True
Seed: 42
Batch Size: 352
Initial Lr: 0.001
Total Epochs Ran: 17
Early Stopped: True
Training Time Seconds: 9935.389509916306
Num Parameters: 21666049
Device: NVIDIA A100-SXM4-40GB
Run Id: vit-tuned-sota

Training Configuration

Epochs: 17
Batch size: 352
Learning rate (initial): 0.001

Training Logs (Per Epoch)

Epoch	Train Loss	Train Acc	Val Loss	Val Acc	LR
1	0.5760	0.7394	0.4960	0.7463	0.000100
2	0.4235	0.8045	0.4166	0.7999	0.000200
3	0.3990	0.8191	0.4240	0.7902	0.000300
4	0.3827	0.8273	0.3552	0.8308	0.000400
5	0.3745	0.8315	0.3966	0.8094	0.000500
6	0.3716	0.8328	0.4255	0.7925	0.000600
7	0.3632	0.8375	0.3360	0.8483	0.000700
8	0.3603	0.8397	0.4131	0.7990	0.000800
9	0.3562	0.8418	0.3642	0.8295	0.000900
10	0.3505	0.8442	0.3885	0.8094	0.001000
11	0.3432	0.8490	0.4165	0.7999	0.001000
12	0.3381	0.8514	0.3754	0.8293	0.001000
13	0.3334	0.8536	0.3611	0.8345	0.000999
14	0.3292	0.8557	0.4204	0.8109	0.000998
15	0.3205	0.8598	0.3687	0.8343	0.000996
16	nan	0.8588	0.3862	0.8230	0.000994
17	0.3147	0.8636	0.3794	0.8328	0.000991

Created: Apr 29, 2025
Updated: Apr 29, 2025