Hugging Face's logo

hkivancoral
/
hushem_40x_deit_small_adamax_00001_fold4

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
hushem_40x_deit_small_adamax_00001_fold4 / README.md
hkivancoral's picture
hkivancoral
End of training
68a7be2
preview code
|
raw
history blame contribute delete
4.88 kB
metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: hushem_40x_deit_small_adamax_00001_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: 0.9285714285714286

hushem_40x_deit_small_adamax_00001_fold4

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: 0.4871
  • Accuracy: 0.9286

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: 1e-05
  • 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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3231 1.0 219 0.5052 0.8333
0.0379 2.0 438 0.1942 0.9524
0.0035 3.0 657 0.1985 0.9524
0.0013 4.0 876 0.1951 0.9524
0.0011 5.0 1095 0.2264 0.9524
0.0004 6.0 1314 0.2512 0.9286
0.0002 7.0 1533 0.2460 0.9286
0.0002 8.0 1752 0.2596 0.9286
0.0001 9.0 1971 0.2767 0.9286
0.0001 10.0 2190 0.2928 0.9286
0.0001 11.0 2409 0.2970 0.9286
0.0001 12.0 2628 0.2820 0.9286
0.0001 13.0 2847 0.3043 0.9286
0.0 14.0 3066 0.3118 0.9286
0.0 15.0 3285 0.3261 0.9286
0.0 16.0 3504 0.3432 0.9286
0.0 17.0 3723 0.3644 0.9286
0.0 18.0 3942 0.3650 0.9286
0.0 19.0 4161 0.3445 0.9286
0.0 20.0 4380 0.3724 0.9286
0.0 21.0 4599 0.3804 0.9286
0.0 22.0 4818 0.3614 0.9286
0.0 23.0 5037 0.3623 0.9286
0.0 24.0 5256 0.3788 0.9286
0.0 25.0 5475 0.3915 0.9286
0.0 26.0 5694 0.3845 0.9286
0.0 27.0 5913 0.4164 0.9286
0.0 28.0 6132 0.4005 0.9286
0.0 29.0 6351 0.4219 0.9286
0.0 30.0 6570 0.4046 0.9286
0.0 31.0 6789 0.4132 0.9286
0.0 32.0 7008 0.4320 0.9286
0.0 33.0 7227 0.4247 0.9286
0.0 34.0 7446 0.4486 0.9286
0.0 35.0 7665 0.4281 0.9286
0.0 36.0 7884 0.4371 0.9286
0.0 37.0 8103 0.4603 0.9286
0.0 38.0 8322 0.4397 0.9286
0.0 39.0 8541 0.4445 0.9286
0.0 40.0 8760 0.4589 0.9286
0.0 41.0 8979 0.4480 0.9286
0.0 42.0 9198 0.4530 0.9286
0.0 43.0 9417 0.4708 0.9286
0.0 44.0 9636 0.4852 0.9286
0.0 45.0 9855 0.4662 0.9286
0.0 46.0 10074 0.4885 0.9286
0.0 47.0 10293 0.4916 0.9286
0.0 48.0 10512 0.4924 0.9286
0.0 49.0 10731 0.4929 0.9286
0.0 50.0 10950 0.4871 0.9286

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.12.0
  • Tokenizers 0.13.2