metadata

license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: banknote18k
    results: []

banknote18k

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0096
Accuracy: 0.9987

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: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4947	0.12	100	0.3407	0.9451
0.423	0.23	200	0.2200	0.9451
0.2237	0.35	300	0.1613	0.9536
0.2806	0.46	400	0.0884	0.9810
0.1188	0.58	500	0.0512	0.9895
0.3279	0.7	600	0.0568	0.9876
0.1054	0.81	700	0.0342	0.9928
0.0924	0.93	800	0.0536	0.9863
0.1068	1.05	900	0.0746	0.9804
0.213	1.16	1000	0.0340	0.9948
0.159	1.28	1100	0.0426	0.9882
0.1048	1.39	1200	0.0248	0.9948
0.1493	1.51	1300	0.0154	0.9974
0.1274	1.63	1400	0.0394	0.9922
0.0915	1.74	1500	0.0422	0.9882
0.0598	1.86	1600	0.0219	0.9948
0.1241	1.97	1700	0.0173	0.9948
0.1249	2.09	1800	0.0179	0.9954
0.0131	2.21	1900	0.0124	0.9961
0.0392	2.32	2000	0.0123	0.9967
0.0655	2.44	2100	0.0223	0.9948
0.0355	2.56	2200	0.0256	0.9941
0.0335	2.67	2300	0.0147	0.9967
0.0618	2.79	2400	0.0123	0.9974
0.0476	2.9	2500	0.0110	0.9980
0.0452	3.02	2600	0.0192	0.9967
0.0104	3.14	2700	0.0184	0.9967
0.036	3.25	2800	0.0122	0.9974
0.0358	3.37	2900	0.0104	0.9987
0.054	3.48	3000	0.0101	0.9987
0.0395	3.6	3100	0.0132	0.9967
0.0367	3.72	3200	0.0096	0.9987
0.0261	3.83	3300	0.0101	0.9980
0.0017	3.95	3400	0.0096	0.9987

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3