vit-base_rvl_cdip-N1K_aAURC_64 – AI Model by bdpc | AlphaNeural AI

You can deploy this model and start earning money today!

bdpc/
vit-base_rvl_cdip-N1K_aAURC_64

like

0

image-classification

generated_from_trainer

jordyvl/vit-base_rvl-cdip

autotrain_compatible

endpoints_compatible

Views

No views yet

vit-base_rvl_cdip-N1K_aAURC_64

This model is a fine-tuned version of jordyvl/vit-base_rvl-cdip on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4857
Accuracy: 0.8892
Brier Loss: 0.1843
Nll: 0.9506
F1 Micro: 0.8892
F1 Macro: 0.8895
Ece: 0.0837
Aurc: 0.0193

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: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Brier Loss	Nll	F1 Micro	F1 Macro	Ece	Aurc
No log	1.0	250	0.3824	0.888	0.1700	1.1756	0.888	0.8884	0.0548	0.0185
0.1403	2.0	500	0.3988	0.8925	0.1681	1.1230	0.8925	0.8936	0.0549	0.0199
0.1403	3.0	750	0.4099	0.8865	0.1756	1.0948	0.8865	0.8868	0.0672	0.0187
0.0442	4.0	1000	0.4297	0.8925	0.1747	1.0568	0.8925	0.8931	0.0685	0.0191
0.0442	5.0	1250	0.4467	0.8925	0.1775	1.0202	0.8925	0.8928	0.0734	0.0194
0.0119	6.0	1500	0.4612	0.8908	0.1808	0.9834	0.8907	0.8914	0.0772	0.0191
0.0119	7.0	1750	0.4762	0.8882	0.1845	0.9761	0.8882	0.8885	0.0827	0.0197
0.0062	8.0	2000	0.4763	0.892	0.1824	0.9652	0.892	0.8923	0.0789	0.0192
0.0062	9.0	2250	0.4854	0.8892	0.1844	0.9509	0.8892	0.8895	0.0834	0.0193
0.0051	10.0	2500	0.4857	0.8892	0.1843	0.9506	0.8892	0.8895	0.0837	0.0193

Framework versions

Transformers 4.33.3
Pytorch 2.2.0.dev20231002
Datasets 2.7.1
Tokenizers 0.13.3