metadata

license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_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: 0.3950583763236492

Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold1

This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.8160
Accuracy: 0.3951

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
2.4438	1.0	924	2.4927	0.1898
2.3969	2.0	1848	2.3384	0.2389
2.2609	3.0	2772	2.2168	0.2878
2.0421	4.0	3696	2.1285	0.3068
2.0227	5.0	4620	2.0634	0.3296
1.99	6.0	5544	2.0084	0.3397
1.9954	7.0	6468	1.9664	0.3549
2.0727	8.0	7392	1.9354	0.3652
2.0158	9.0	8316	1.9072	0.3704
1.8488	10.0	9240	1.8880	0.3750
1.8985	11.0	10164	1.8721	0.3790
1.7309	12.0	11088	1.8576	0.3812
1.8129	13.0	12012	1.8465	0.3899
1.7599	14.0	12936	1.8384	0.3866
1.7902	15.0	13860	1.8309	0.3894
1.7502	16.0	14784	1.8250	0.3932
1.7034	17.0	15708	1.8221	0.3934
1.8587	18.0	16632	1.8187	0.3940
1.8137	19.0	17556	1.8165	0.3942
1.9039	20.0	18480	1.8160	0.3951

Framework versions

Transformers 4.40.1
Pytorch 2.1.0
Datasets 2.19.0
Tokenizers 0.19.1