metadata

license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: hushem_conflu_deneme_fold4
    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: 0.7380952380952381

hushem_conflu_deneme_fold4

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: 0.8165
Accuracy: 0.7381

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: 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
No log	1.0	6	1.7088	0.2381
1.9076	2.0	12	1.4617	0.2381
1.9076	3.0	18	1.4512	0.2619
1.4689	4.0	24	1.3283	0.2381
1.3599	5.0	30	1.0112	0.6667
1.3599	6.0	36	1.1598	0.3810
1.2233	7.0	42	1.4323	0.4524
1.2233	8.0	48	0.9658	0.6667
1.0502	9.0	54	0.9166	0.6429
0.8636	10.0	60	0.8181	0.6190
0.8636	11.0	66	1.2729	0.5238
0.8856	12.0	72	0.7434	0.7381
0.8856	13.0	78	0.6840	0.7143
0.6672	14.0	84	0.9596	0.5238
0.5861	15.0	90	0.7243	0.7381
0.5861	16.0	96	0.8378	0.7143
0.4357	17.0	102	0.8165	0.7381
0.4357	18.0	108	0.8165	0.7381
0.4614	19.0	114	0.8165	0.7381
0.431	20.0	120	0.8165	0.7381

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1