metadata

license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-student_two_classes
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8

swin-tiny-patch4-window7-224-finetuned-student_two_classes

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.6649
Accuracy: 0.8

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: 5e-06
train_batch_size: 32
eval_batch_size: 32
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3416	1.0	13	0.6767	0.81
0.2745	2.0	26	0.7166	0.81
0.2482	3.0	39	0.7644	0.83
0.2664	4.0	52	0.7142	0.81
0.2372	5.0	65	0.8010	0.85
0.2238	6.0	78	0.8655	0.86
0.1687	7.0	91	0.8156	0.83
0.209	8.0	104	0.8460	0.83
0.4251	9.0	117	0.7301	0.81
0.4392	10.0	130	0.6775	0.78
0.3285	11.0	143	0.7145	0.81
0.3178	12.0	156	0.7431	0.83
0.4715	13.0	169	0.6973	0.81
0.373	14.0	182	0.6912	0.81
0.3378	15.0	195	0.7018	0.82
0.3867	16.0	208	0.6885	0.81
0.3525	17.0	221	0.6761	0.81
0.4253	18.0	234	0.6643	0.8
0.325	19.0	247	0.6643	0.8
0.372	20.0	260	0.6649	0.8

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1