metadata

license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya1_Adamax_1-e4_20Epoch_Deit-small-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: 0.6046701058919359

Boya1_Adamax_1-e4_20Epoch_Deit-small-patch16_fold1

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

Loss: 3.6631
Accuracy: 0.6047

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: 0.0001
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
1.2053	1.0	924	1.3479	0.5436
1.0533	2.0	1848	1.2465	0.5745
0.9598	3.0	2772	1.2623	0.5786
0.5046	4.0	3696	1.2915	0.5987
0.3319	5.0	4620	1.4822	0.5906
0.2366	6.0	5544	1.7116	0.5854
0.0946	7.0	6468	2.0587	0.5873
0.0513	8.0	7392	2.3576	0.5971
0.0119	9.0	8316	2.5882	0.5916
0.005	10.0	9240	2.8824	0.5900
0.0005	11.0	10164	2.9269	0.6036
0.0002	12.0	11088	3.1123	0.5979
0.002	13.0	12012	3.1469	0.5965
0.0001	14.0	12936	3.1949	0.6009
0.0001	15.0	13860	3.2471	0.6033
0.0	16.0	14784	3.3448	0.6036
0.0	17.0	15708	3.4378	0.6047
0.0	18.0	16632	3.5318	0.6047
0.0	19.0	17556	3.6207	0.6041
0.0	20.0	18480	3.6631	0.6047

Framework versions

Transformers 4.40.1
Pytorch 2.1.0
Datasets 2.19.0
Tokenizers 0.19.1