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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: vit-base-patch16-224-in21k-finetuned-papsmear |
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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: 0.9338235294117647 |
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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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# vit-base-patch16-224-in21k-finetuned-papsmear |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2870 |
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- Accuracy: 0.9338 |
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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: 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 | 0.9231 | 9 | 1.7879 | 0.2059 | |
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| 1.8037 | 1.9487 | 19 | 1.6485 | 0.4044 | |
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| 1.6961 | 2.9744 | 29 | 1.4882 | 0.3971 | |
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| 1.5407 | 4.0 | 39 | 1.3069 | 0.5221 | |
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| 1.3308 | 4.9231 | 48 | 1.1339 | 0.6029 | |
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| 1.1074 | 5.9487 | 58 | 0.9396 | 0.75 | |
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| 0.9162 | 6.9744 | 68 | 0.8551 | 0.7647 | |
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| 0.8174 | 8.0 | 78 | 0.8291 | 0.7574 | |
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| 0.7135 | 8.9231 | 87 | 0.7505 | 0.7941 | |
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| 0.6222 | 9.9487 | 97 | 0.6434 | 0.8456 | |
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| 0.5445 | 10.9744 | 107 | 0.5996 | 0.8529 | |
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| 0.4935 | 12.0 | 117 | 0.5514 | 0.8529 | |
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| 0.4131 | 12.9231 | 126 | 0.5029 | 0.8603 | |
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| 0.4012 | 13.9487 | 136 | 0.5566 | 0.8382 | |
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| 0.3689 | 14.9744 | 146 | 0.5533 | 0.8382 | |
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| 0.3533 | 16.0 | 156 | 0.4232 | 0.8971 | |
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| 0.2954 | 16.9231 | 165 | 0.4589 | 0.8897 | |
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| 0.2907 | 17.9487 | 175 | 0.4223 | 0.8971 | |
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| 0.2804 | 18.9744 | 185 | 0.4056 | 0.8971 | |
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| 0.2469 | 20.0 | 195 | 0.3904 | 0.9118 | |
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| 0.2643 | 20.9231 | 204 | 0.3866 | 0.9044 | |
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| 0.2212 | 21.9487 | 214 | 0.4173 | 0.875 | |
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| 0.2476 | 22.9744 | 224 | 0.6001 | 0.8015 | |
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| 0.2347 | 24.0 | 234 | 0.3900 | 0.9044 | |
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| 0.207 | 24.9231 | 243 | 0.4033 | 0.8897 | |
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| 0.1803 | 25.9487 | 253 | 0.3510 | 0.9265 | |
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| 0.1979 | 26.9744 | 263 | 0.3723 | 0.9191 | |
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| 0.1821 | 28.0 | 273 | 0.4320 | 0.8824 | |
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| 0.1992 | 28.9231 | 282 | 0.3557 | 0.9118 | |
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| 0.2154 | 29.9487 | 292 | 0.3362 | 0.9191 | |
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| 0.1801 | 30.9744 | 302 | 0.4358 | 0.875 | |
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| 0.1794 | 32.0 | 312 | 0.3500 | 0.9191 | |
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| 0.1566 | 32.9231 | 321 | 0.3046 | 0.9265 | |
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| 0.1432 | 33.9487 | 331 | 0.3239 | 0.9265 | |
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| 0.145 | 34.9744 | 341 | 0.3311 | 0.9338 | |
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| 0.1578 | 36.0 | 351 | 0.3029 | 0.9338 | |
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| 0.1511 | 36.9231 | 360 | 0.3010 | 0.9338 | |
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| 0.139 | 37.9487 | 370 | 0.2982 | 0.9265 | |
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| 0.1294 | 38.9744 | 380 | 0.3261 | 0.9191 | |
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| 0.1263 | 40.0 | 390 | 0.2932 | 0.9338 | |
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| 0.1263 | 40.9231 | 399 | 0.2944 | 0.9338 | |
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| 0.1216 | 41.9487 | 409 | 0.2867 | 0.9338 | |
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| 0.1199 | 42.9744 | 419 | 0.2887 | 0.9338 | |
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| 0.128 | 44.0 | 429 | 0.2825 | 0.9338 | |
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| 0.1115 | 44.9231 | 438 | 0.2880 | 0.9338 | |
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| 0.1179 | 45.9487 | 448 | 0.2871 | 0.9338 | |
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| 0.12 | 46.1538 | 450 | 0.2870 | 0.9338 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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