metadata

license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: vit-cxr4
    results: []

vit-cxr4

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

Loss: 0.3774
Precision: 0.8587
Recall: 0.9317
F1: 0.8937
Accuracy: 0.8924

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: 3e-05
train_batch_size: 96
eval_batch_size: 64
seed: 17
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3151	0.31	100	0.3317	0.8152	0.9143	0.8619	0.8552
0.319	0.63	200	0.3048	0.8670	0.8514	0.8591	0.8620
0.2926	0.94	300	0.2867	0.8580	0.8662	0.8621	0.8631
0.1884	1.25	400	0.2635	0.8468	0.9381	0.8901	0.8856
0.234	1.57	500	0.2639	0.8232	0.9677	0.8896	0.8814
0.2349	1.88	600	0.2478	0.8530	0.9328	0.8911	0.8874
0.1476	2.19	700	0.2560	0.8584	0.9297	0.8926	0.8895
0.1289	2.51	800	0.2698	0.8809	0.8916	0.8862	0.8869
0.1579	2.82	900	0.2614	0.8879	0.8715	0.8796	0.8822
0.0745	3.13	1000	0.2783	0.8854	0.8905	0.8880	0.8889
0.0697	3.45	1100	0.2844	0.8893	0.8879	0.8886	0.8900
0.0602	3.76	1200	0.3213	0.8797	0.8932	0.8864	0.8869
0.0246	4.08	1300	0.3393	0.8753	0.9096	0.8921	0.8913
0.0301	4.39	1400	0.3593	0.8644	0.9307	0.8964	0.8937
0.0348	4.7	1500	0.3804	0.8653	0.9344	0.8986	0.8957
0.011	5.02	1600	0.3897	0.8622	0.9365	0.8978	0.8947
0.0077	5.33	1700	0.4088	0.8754	0.9180	0.8962	0.8950
0.0064	5.64	1800	0.4281	0.8780	0.9170	0.8971	0.8960
0.0031	5.96	1900	0.4289	0.8736	0.9207	0.8965	0.8950

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0