Hugging Face's logo

hkivancoral
/
smids_10x_deit_tiny_sgd_001_fold1

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
smids_10x_deit_tiny_sgd_001_fold1 / README.md
hkivancoral's picture
hkivancoral
End of training
03702f6
preview code
|
raw
history blame contribute delete
4.86 kB
metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: smids_10x_deit_tiny_sgd_001_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: 0.8714524207011686

smids_10x_deit_tiny_sgd_001_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: 0.3411
  • Accuracy: 0.8715

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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5089 1.0 751 0.6112 0.7429
0.3967 2.0 1502 0.4763 0.7930
0.2926 3.0 2253 0.3983 0.8314
0.2707 4.0 3004 0.3655 0.8431
0.3017 5.0 3755 0.3388 0.8598
0.2883 6.0 4506 0.3239 0.8581
0.2607 7.0 5257 0.3147 0.8681
0.2345 8.0 6008 0.3166 0.8564
0.2342 9.0 6759 0.3080 0.8765
0.2448 10.0 7510 0.3026 0.8715
0.2489 11.0 8261 0.3046 0.8664
0.2253 12.0 9012 0.3048 0.8731
0.1846 13.0 9763 0.3033 0.8681
0.1475 14.0 10514 0.3005 0.8698
0.1911 15.0 11265 0.2987 0.8731
0.1765 16.0 12016 0.3037 0.8664
0.2371 17.0 12767 0.3023 0.8698
0.1758 18.0 13518 0.3012 0.8731
0.2258 19.0 14269 0.3050 0.8698
0.1902 20.0 15020 0.3050 0.8681
0.1077 21.0 15771 0.3133 0.8698
0.1647 22.0 16522 0.3182 0.8715
0.1389 23.0 17273 0.3149 0.8731
0.1858 24.0 18024 0.3136 0.8664
0.1711 25.0 18775 0.3139 0.8631
0.191 26.0 19526 0.3138 0.8648
0.181 27.0 20277 0.3209 0.8715
0.2185 28.0 21028 0.3215 0.8748
0.1776 29.0 21779 0.3185 0.8715
0.135 30.0 22530 0.3255 0.8681
0.1282 31.0 23281 0.3235 0.8715
0.1784 32.0 24032 0.3244 0.8698
0.2006 33.0 24783 0.3311 0.8581
0.106 34.0 25534 0.3280 0.8715
0.1426 35.0 26285 0.3297 0.8681
0.1309 36.0 27036 0.3304 0.8614
0.2379 37.0 27787 0.3292 0.8748
0.1297 38.0 28538 0.3352 0.8698
0.0635 39.0 29289 0.3365 0.8664
0.1936 40.0 30040 0.3376 0.8698
0.1143 41.0 30791 0.3368 0.8731
0.1251 42.0 31542 0.3385 0.8664
0.1338 43.0 32293 0.3411 0.8681
0.1093 44.0 33044 0.3395 0.8681
0.1208 45.0 33795 0.3395 0.8715
0.1467 46.0 34546 0.3416 0.8698
0.0894 47.0 35297 0.3413 0.8698
0.1318 48.0 36048 0.3412 0.8681
0.0983 49.0 36799 0.3410 0.8715
0.1226 50.0 37550 0.3411 0.8715

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.1+cu121
  • Datasets 2.12.0
  • Tokenizers 0.13.2