README.md

metadata

license: apache-2.0
base_model: microsoft/swin-large-patch4-window7-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya1_SGD_1e3_20Epoch_Swin-large-224_fold1
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.3288080369264187

Boya1_SGD_1e3_20Epoch_Swin-large-224_fold1

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

• Loss: 2.1316
• Accuracy: 0.3288

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: 0.001
• 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
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.6134	1.0	924	2.5724	0.1941
2.5066	2.0	1848	2.4917	0.1947
2.5572	3.0	2772	2.4417	0.1971
2.3516	4.0	3696	2.4048	0.2080
2.4257	5.0	4620	2.3743	0.2332
2.3129	6.0	5544	2.3404	0.2411
2.2992	7.0	6468	2.3155	0.2636
2.266	8.0	7392	2.2914	0.2683
2.2389	9.0	8316	2.2655	0.2778
2.2861	10.0	9240	2.2421	0.2873
2.2192	11.0	10164	2.2250	0.2905
2.2057	12.0	11088	2.2046	0.2984
2.0519	13.0	12012	2.1880	0.3046
2.1151	14.0	12936	2.1736	0.3144
2.1116	15.0	13860	2.1599	0.3204
2.0726	16.0	14784	2.1517	0.3234
2.1017	17.0	15708	2.1408	0.3272
2.051	18.0	16632	2.1358	0.3285
2.0423	19.0	17556	2.1327	0.3296
2.0517	20.0	18480	2.1316	0.3288

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.1+cu121
• Datasets 2.21.0
• Tokenizers 0.13.2