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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: beit-base-patch16-224-fold4 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8227848101265823 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# beit-base-patch16-224-fold4 |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8625 |
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- Accuracy: 0.8228 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.8571 | 3 | 0.8664 | 0.3797 | |
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| No log | 2.0 | 7 | 0.8144 | 0.4810 | |
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| 0.7345 | 2.8571 | 10 | 0.6451 | 0.5823 | |
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| 0.7345 | 4.0 | 14 | 0.7268 | 0.5190 | |
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| 0.7345 | 4.8571 | 17 | 0.5731 | 0.7342 | |
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| 0.6447 | 6.0 | 21 | 0.6948 | 0.5316 | |
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| 0.6447 | 6.8571 | 24 | 0.5315 | 0.6962 | |
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| 0.6447 | 8.0 | 28 | 0.5292 | 0.6835 | |
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| 0.5582 | 8.8571 | 31 | 0.6226 | 0.5823 | |
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| 0.5582 | 10.0 | 35 | 0.5479 | 0.6329 | |
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| 0.5582 | 10.8571 | 38 | 0.5230 | 0.7975 | |
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| 0.4807 | 12.0 | 42 | 0.6146 | 0.6709 | |
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| 0.4807 | 12.8571 | 45 | 0.6346 | 0.6709 | |
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| 0.4807 | 14.0 | 49 | 1.0584 | 0.5823 | |
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| 0.4441 | 14.8571 | 52 | 0.4716 | 0.7848 | |
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| 0.4441 | 16.0 | 56 | 0.4454 | 0.7595 | |
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| 0.4441 | 16.8571 | 59 | 0.5688 | 0.7595 | |
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| 0.3829 | 18.0 | 63 | 0.5233 | 0.7975 | |
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| 0.3829 | 18.8571 | 66 | 0.5291 | 0.7975 | |
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| 0.3352 | 20.0 | 70 | 0.4981 | 0.7848 | |
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| 0.3352 | 20.8571 | 73 | 0.8590 | 0.7468 | |
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| 0.3352 | 22.0 | 77 | 0.5201 | 0.7975 | |
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| 0.341 | 22.8571 | 80 | 0.6530 | 0.7468 | |
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| 0.341 | 24.0 | 84 | 0.5732 | 0.7848 | |
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| 0.341 | 24.8571 | 87 | 0.6532 | 0.7975 | |
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| 0.2554 | 26.0 | 91 | 0.5656 | 0.7722 | |
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| 0.2554 | 26.8571 | 94 | 0.8085 | 0.7595 | |
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| 0.2554 | 28.0 | 98 | 0.4826 | 0.7848 | |
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| 0.325 | 28.8571 | 101 | 0.8227 | 0.7468 | |
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| 0.325 | 30.0 | 105 | 0.5349 | 0.7975 | |
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| 0.325 | 30.8571 | 108 | 0.7056 | 0.7722 | |
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| 0.2572 | 32.0 | 112 | 0.5415 | 0.7848 | |
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| 0.2572 | 32.8571 | 115 | 0.5953 | 0.7848 | |
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| 0.2572 | 34.0 | 119 | 0.5884 | 0.7848 | |
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| 0.1994 | 34.8571 | 122 | 0.5971 | 0.7975 | |
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| 0.1994 | 36.0 | 126 | 0.8481 | 0.7468 | |
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| 0.1994 | 36.8571 | 129 | 0.6107 | 0.7595 | |
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| 0.209 | 38.0 | 133 | 0.9242 | 0.7848 | |
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| 0.209 | 38.8571 | 136 | 0.7106 | 0.7722 | |
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| 0.188 | 40.0 | 140 | 0.9581 | 0.7722 | |
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| 0.188 | 40.8571 | 143 | 0.9282 | 0.7722 | |
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| 0.188 | 42.0 | 147 | 1.0447 | 0.7848 | |
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| 0.1982 | 42.8571 | 150 | 0.9748 | 0.7722 | |
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| 0.1982 | 44.0 | 154 | 0.7132 | 0.7848 | |
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| 0.1982 | 44.8571 | 157 | 0.6957 | 0.7848 | |
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| 0.1799 | 46.0 | 161 | 0.8674 | 0.7848 | |
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| 0.1799 | 46.8571 | 164 | 0.9036 | 0.7848 | |
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| 0.1799 | 48.0 | 168 | 0.9910 | 0.7848 | |
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| 0.1502 | 48.8571 | 171 | 1.0821 | 0.7722 | |
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| 0.1502 | 50.0 | 175 | 0.8117 | 0.7848 | |
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| 0.1502 | 50.8571 | 178 | 0.9037 | 0.7722 | |
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| 0.1591 | 52.0 | 182 | 0.8272 | 0.7722 | |
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| 0.1591 | 52.8571 | 185 | 1.0109 | 0.7848 | |
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| 0.1591 | 54.0 | 189 | 0.8490 | 0.7722 | |
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| 0.1588 | 54.8571 | 192 | 0.8973 | 0.7722 | |
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| 0.1588 | 56.0 | 196 | 0.9084 | 0.7722 | |
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| 0.1588 | 56.8571 | 199 | 0.8034 | 0.7595 | |
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| 0.1353 | 58.0 | 203 | 0.8885 | 0.7848 | |
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| 0.1353 | 58.8571 | 206 | 1.0837 | 0.7848 | |
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| 0.1308 | 60.0 | 210 | 0.8627 | 0.7975 | |
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| 0.1308 | 60.8571 | 213 | 0.9842 | 0.8101 | |
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| 0.1308 | 62.0 | 217 | 0.9966 | 0.7975 | |
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| 0.1402 | 62.8571 | 220 | 0.9639 | 0.7848 | |
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| 0.1402 | 64.0 | 224 | 1.0104 | 0.7848 | |
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| 0.1402 | 64.8571 | 227 | 0.8940 | 0.7722 | |
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| 0.1301 | 66.0 | 231 | 0.9349 | 0.7848 | |
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| 0.1301 | 66.8571 | 234 | 1.1485 | 0.7848 | |
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| 0.1301 | 68.0 | 238 | 1.0021 | 0.7848 | |
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| 0.1399 | 68.8571 | 241 | 0.8971 | 0.7975 | |
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| 0.1399 | 70.0 | 245 | 0.8604 | 0.7975 | |
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| 0.1399 | 70.8571 | 248 | 0.8625 | 0.8228 | |
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| 0.1203 | 72.0 | 252 | 1.0301 | 0.7975 | |
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| 0.1203 | 72.8571 | 255 | 1.2355 | 0.7722 | |
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| 0.1203 | 74.0 | 259 | 1.0716 | 0.7848 | |
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| 0.1385 | 74.8571 | 262 | 0.9598 | 0.7975 | |
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| 0.1385 | 76.0 | 266 | 0.9965 | 0.7975 | |
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| 0.1385 | 76.8571 | 269 | 1.1018 | 0.7975 | |
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| 0.115 | 78.0 | 273 | 1.0895 | 0.7975 | |
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| 0.115 | 78.8571 | 276 | 1.0261 | 0.7848 | |
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| 0.1227 | 80.0 | 280 | 0.9800 | 0.7975 | |
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| 0.1227 | 80.8571 | 283 | 0.9960 | 0.7848 | |
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| 0.1227 | 82.0 | 287 | 1.0251 | 0.7848 | |
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| 0.1044 | 82.8571 | 290 | 1.0236 | 0.7848 | |
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| 0.1044 | 84.0 | 294 | 1.0139 | 0.7848 | |
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| 0.1044 | 84.8571 | 297 | 1.0073 | 0.7848 | |
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| 0.1246 | 85.7143 | 300 | 1.0066 | 0.7848 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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