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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: hushem_1x_beit_base_sgd_00001_fold5 |
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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: test |
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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: 0.24390243902439024 |
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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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# hushem_1x_beit_base_sgd_00001_fold5 |
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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: 1.6258 |
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- Accuracy: 0.2439 |
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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: 1e-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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- 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: 50 |
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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 | 1.0 | 6 | 1.6353 | 0.2439 | |
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| 1.5783 | 2.0 | 12 | 1.6348 | 0.2439 | |
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| 1.5783 | 3.0 | 18 | 1.6344 | 0.2439 | |
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| 1.5876 | 4.0 | 24 | 1.6339 | 0.2439 | |
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| 1.5772 | 5.0 | 30 | 1.6335 | 0.2439 | |
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| 1.5772 | 6.0 | 36 | 1.6330 | 0.2439 | |
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| 1.5977 | 7.0 | 42 | 1.6326 | 0.2439 | |
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| 1.5977 | 8.0 | 48 | 1.6322 | 0.2439 | |
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| 1.5317 | 9.0 | 54 | 1.6318 | 0.2439 | |
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| 1.5968 | 10.0 | 60 | 1.6314 | 0.2439 | |
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| 1.5968 | 11.0 | 66 | 1.6311 | 0.2439 | |
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| 1.549 | 12.0 | 72 | 1.6307 | 0.2439 | |
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| 1.549 | 13.0 | 78 | 1.6303 | 0.2439 | |
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| 1.5721 | 14.0 | 84 | 1.6300 | 0.2439 | |
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| 1.5369 | 15.0 | 90 | 1.6297 | 0.2439 | |
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| 1.5369 | 16.0 | 96 | 1.6294 | 0.2439 | |
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| 1.5705 | 17.0 | 102 | 1.6291 | 0.2439 | |
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| 1.5705 | 18.0 | 108 | 1.6288 | 0.2439 | |
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| 1.5679 | 19.0 | 114 | 1.6286 | 0.2439 | |
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| 1.5656 | 20.0 | 120 | 1.6284 | 0.2439 | |
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| 1.5656 | 21.0 | 126 | 1.6281 | 0.2439 | |
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| 1.5685 | 22.0 | 132 | 1.6279 | 0.2439 | |
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| 1.5685 | 23.0 | 138 | 1.6277 | 0.2439 | |
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| 1.5419 | 24.0 | 144 | 1.6275 | 0.2439 | |
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| 1.5718 | 25.0 | 150 | 1.6273 | 0.2439 | |
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| 1.5718 | 26.0 | 156 | 1.6271 | 0.2439 | |
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| 1.5745 | 27.0 | 162 | 1.6269 | 0.2439 | |
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| 1.5745 | 28.0 | 168 | 1.6268 | 0.2439 | |
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| 1.5571 | 29.0 | 174 | 1.6267 | 0.2439 | |
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| 1.5843 | 30.0 | 180 | 1.6265 | 0.2439 | |
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| 1.5843 | 31.0 | 186 | 1.6264 | 0.2439 | |
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| 1.5761 | 32.0 | 192 | 1.6263 | 0.2439 | |
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| 1.5761 | 33.0 | 198 | 1.6262 | 0.2439 | |
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| 1.5292 | 34.0 | 204 | 1.6261 | 0.2439 | |
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| 1.5827 | 35.0 | 210 | 1.6261 | 0.2439 | |
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| 1.5827 | 36.0 | 216 | 1.6260 | 0.2439 | |
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| 1.5796 | 37.0 | 222 | 1.6259 | 0.2439 | |
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| 1.5796 | 38.0 | 228 | 1.6259 | 0.2439 | |
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| 1.5699 | 39.0 | 234 | 1.6259 | 0.2439 | |
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| 1.5472 | 40.0 | 240 | 1.6258 | 0.2439 | |
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| 1.5472 | 41.0 | 246 | 1.6258 | 0.2439 | |
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| 1.5603 | 42.0 | 252 | 1.6258 | 0.2439 | |
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| 1.5603 | 43.0 | 258 | 1.6258 | 0.2439 | |
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| 1.5805 | 44.0 | 264 | 1.6258 | 0.2439 | |
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| 1.5679 | 45.0 | 270 | 1.6258 | 0.2439 | |
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| 1.5679 | 46.0 | 276 | 1.6258 | 0.2439 | |
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| 1.5821 | 47.0 | 282 | 1.6258 | 0.2439 | |
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| 1.5821 | 48.0 | 288 | 1.6258 | 0.2439 | |
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| 1.5058 | 49.0 | 294 | 1.6258 | 0.2439 | |
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| 1.5509 | 50.0 | 300 | 1.6258 | 0.2439 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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