Hugging Face's logo

BilalMuftuoglu
/
deit-base-distilled-patch16-224-65-fold4

Image Classification
Transformers
TensorBoard
Safetensors
deit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
deit-base-distilled-patch16-224-65-fold4 / README.md
BilalMuftuoglu's picture
BilalMuftuoglu
Model save
97a8e52 verified
preview code
|
raw
history blame
7.78 kB
metadata
license: apache-2.0
base_model: facebook/deit-base-distilled-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: deit-base-distilled-patch16-224-65-fold4
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8169014084507042

deit-base-distilled-patch16-224-65-fold4

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

  • Loss: 0.5748
  • Accuracy: 0.8169

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.9231 3 0.7145 0.5211
No log 1.8462 6 0.7082 0.5070
No log 2.7692 9 0.6889 0.6056
0.6878 4.0 13 0.6703 0.6620
0.6878 4.9231 16 0.6556 0.6761
0.6878 5.8462 19 0.6430 0.6620
0.6203 6.7692 22 0.6250 0.6761
0.6203 8.0 26 0.7464 0.6197
0.6203 8.9231 29 0.6647 0.6056
0.5703 9.8462 32 0.6097 0.7042
0.5703 10.7692 35 0.6261 0.6620
0.5703 12.0 39 0.5926 0.7042
0.5281 12.9231 42 0.5370 0.7465
0.5281 13.8462 45 0.5638 0.7465
0.5281 14.7692 48 0.7175 0.6056
0.4616 16.0 52 0.8917 0.5775
0.4616 16.9231 55 0.6761 0.6761
0.4616 17.8462 58 0.5606 0.7324
0.4943 18.7692 61 0.6963 0.6338
0.4943 20.0 65 0.6462 0.6620
0.4943 20.9231 68 0.6246 0.7183
0.4058 21.8462 71 0.7336 0.6620
0.4058 22.7692 74 0.6270 0.7324
0.4058 24.0 78 0.6097 0.7183
0.3577 24.9231 81 0.6700 0.7606
0.3577 25.8462 84 0.6676 0.7183
0.3577 26.7692 87 0.5475 0.7887
0.2988 28.0 91 0.5383 0.8028
0.2988 28.9231 94 0.5534 0.7183
0.2988 29.8462 97 0.5842 0.8028
0.2595 30.7692 100 0.5965 0.7887
0.2595 32.0 104 0.6220 0.7606
0.2595 32.9231 107 0.6027 0.7606
0.2422 33.8462 110 0.6369 0.7183
0.2422 34.7692 113 0.6033 0.7746
0.2422 36.0 117 0.6912 0.7324
0.1927 36.9231 120 0.6582 0.7887
0.1927 37.8462 123 0.6320 0.7746
0.1927 38.7692 126 0.7532 0.7606
0.2399 40.0 130 0.7909 0.7606
0.2399 40.9231 133 0.6808 0.7465
0.2399 41.8462 136 0.5816 0.7887
0.2399 42.7692 139 0.5474 0.7887
0.2218 44.0 143 0.6310 0.7042
0.2218 44.9231 146 0.6453 0.8028
0.2218 45.8462 149 0.6170 0.7887
0.1817 46.7692 152 0.6034 0.7887
0.1817 48.0 156 0.6350 0.8310
0.1817 48.9231 159 0.6027 0.7887
0.1483 49.8462 162 0.5599 0.8028
0.1483 50.7692 165 0.5817 0.8310
0.1483 52.0 169 0.6086 0.7746
0.1668 52.9231 172 0.5744 0.8169
0.1668 53.8462 175 0.6059 0.7887
0.1668 54.7692 178 0.6455 0.7887
0.1372 56.0 182 0.5367 0.8451
0.1372 56.9231 185 0.5615 0.8169
0.1372 57.8462 188 0.6378 0.8028
0.1485 58.7692 191 0.5687 0.8169
0.1485 60.0 195 0.4897 0.8169
0.1485 60.9231 198 0.4384 0.8451
0.1426 61.8462 201 0.5087 0.7887
0.1426 62.7692 204 0.4757 0.8169
0.1426 64.0 208 0.4373 0.8169
0.1333 64.9231 211 0.4512 0.8169
0.1333 65.8462 214 0.4619 0.7887
0.1333 66.7692 217 0.5520 0.8028
0.1306 68.0 221 0.5161 0.7887
0.1306 68.9231 224 0.5180 0.7606
0.1306 69.8462 227 0.5778 0.8028
0.1327 70.7692 230 0.5933 0.8028
0.1327 72.0 234 0.5222 0.7887
0.1327 72.9231 237 0.5104 0.8169
0.1171 73.8462 240 0.5024 0.8169
0.1171 74.7692 243 0.5060 0.8028
0.1171 76.0 247 0.5267 0.7746
0.1227 76.9231 250 0.4775 0.8169
0.1227 77.8462 253 0.5020 0.8169
0.1227 78.7692 256 0.5243 0.7606
0.1304 80.0 260 0.6195 0.7887
0.1304 80.9231 263 0.5740 0.7606
0.1304 81.8462 266 0.5652 0.8169
0.1304 82.7692 269 0.5750 0.8169
0.1152 84.0 273 0.5829 0.7887
0.1152 84.9231 276 0.5854 0.7887
0.1152 85.8462 279 0.5854 0.7887
0.1069 86.7692 282 0.5826 0.8028
0.1069 88.0 286 0.5839 0.7887
0.1069 88.9231 289 0.5792 0.8169
0.122 89.8462 292 0.5755 0.8169
0.122 90.7692 295 0.5751 0.8169
0.122 92.0 299 0.5748 0.8169
0.1268 92.3077 300 0.5748 0.8169

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1