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_fold2
    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: 0.4181081081081081

Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold2

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: 1.7360
Accuracy: 0.4181

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
2.448	1.0	923	2.4582	0.2016
2.3582	2.0	1846	2.3021	0.2376
2.2617	3.0	2769	2.1666	0.2897
2.0757	4.0	3692	2.0662	0.3235
2.008	5.0	4615	1.9944	0.3449
2.0395	6.0	5538	1.9375	0.3595
1.9087	7.0	6461	1.8952	0.3749
1.9463	8.0	7384	1.8644	0.3805
1.8879	9.0	8307	1.8376	0.3908
1.7446	10.0	9230	1.8140	0.3938
1.7618	11.0	10153	1.7964	0.3965
1.7616	12.0	11076	1.7817	0.4051
1.7296	13.0	11999	1.7702	0.4057
1.8498	14.0	12922	1.7608	0.4124
1.7605	15.0	13845	1.7532	0.4111
1.7119	16.0	14768	1.7468	0.4154
1.7061	17.0	15691	1.7421	0.4157
1.6731	18.0	16614	1.7387	0.4178
1.5776	19.0	17537	1.7366	0.4189
1.5522	20.0	18460	1.7360	0.4181

Framework versions

Transformers 4.40.1
Pytorch 2.1.0
Datasets 2.19.0
Tokenizers 0.19.1