metadata

language:
  - eng
license: apache-2.0
base_model: facebook/dinov2-large
tags:
  - multilabel-image-classification
  - multilabel
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: dino-large-2023_12_06-with_custom_head
    results: []

dino-large-2023_12_06-with_custom_head

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

Loss: 0.2014
F1 Micro: 0.8291
F1 Macro: 0.8015
Roc Auc: 0.9029
Accuracy: 0.5132
Learning Rate: 0.001

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: 0.01
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 14

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	Roc Auc	Accuracy	Rate
0.4706	1.0	536	0.4533	0.7389	0.6876	0.8316	0.4269	0.01
0.4045	2.0	1072	0.4262	0.7669	0.7188	0.8634	0.4391	0.01
0.3973	3.0	1608	0.4722	0.7601	0.7176	0.8372	0.4537	0.01
0.3961	4.0	2144	0.6075	0.7528	0.6913	0.8724	0.3762	0.01
0.3751	5.0	2680	0.3916	0.7884	0.7511	0.8925	0.4352	0.01
0.365	6.0	3216	0.5256	0.7660	0.7066	0.8535	0.4105	0.01
0.3565	7.0	3752	0.5708	0.7293	0.6947	0.8254	0.4101	0.01
0.3807	8.0	4288	0.4770	0.7811	0.7145	0.8609	0.4591	0.01
0.3462	9.0	4824	0.4612	0.7880	0.7522	0.8775	0.4452	0.01
0.38	10.0	5360	0.4559	0.7943	0.7517	0.8747	0.4612	0.01
0.3472	11.0	5896	0.5081	0.7709	0.7315	0.8980	0.4041	0.01
0.3167	12.0	6432	0.2364	0.8268	0.7990	0.8945	0.5141	0.001
0.1322	13.0	6968	0.2222	0.8209	0.7931	0.8951	0.4923	0.001
0.0958	14.0	7504	0.2089	0.8287	0.7975	0.8985	0.5052	0.001

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1