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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-RH
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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: validation
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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: 0.8037383177570093
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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-RH
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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: 0.4340
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- Accuracy: 0.8037
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 40
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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 | 8 | 0.7927 | 0.5888 |
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| 0.8183 | 2.0 | 16 | 0.7412 | 0.5888 |
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| 0.7414 | 3.0 | 24 | 0.6851 | 0.5888 |
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| 0.6837 | 4.0 | 32 | 0.6638 | 0.5888 |
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| 0.6621 | 5.0 | 40 | 0.6619 | 0.5981 |
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| 0.6621 | 6.0 | 48 | 0.6446 | 0.6262 |
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| 0.6538 | 7.0 | 56 | 0.6370 | 0.6729 |
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| 0.641 | 8.0 | 64 | 0.6485 | 0.6636 |
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| 0.628 | 9.0 | 72 | 0.6393 | 0.6449 |
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| 0.6187 | 10.0 | 80 | 0.6409 | 0.5794 |
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| 0.6187 | 11.0 | 88 | 0.6360 | 0.5794 |
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| 0.6075 | 12.0 | 96 | 0.6209 | 0.6355 |
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| 0.6081 | 13.0 | 104 | 0.6377 | 0.6449 |
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| 0.5886 | 14.0 | 112 | 0.5931 | 0.6729 |
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| 0.5945 | 15.0 | 120 | 0.6108 | 0.6636 |
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| 0.5945 | 16.0 | 128 | 0.5846 | 0.7009 |
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| 0.5808 | 17.0 | 136 | 0.5945 | 0.6822 |
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| 0.5636 | 18.0 | 144 | 0.7402 | 0.6636 |
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| 0.5839 | 19.0 | 152 | 0.5661 | 0.6916 |
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| 0.5166 | 20.0 | 160 | 0.5360 | 0.6636 |
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| 0.5166 | 21.0 | 168 | 0.5621 | 0.6729 |
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| 0.5165 | 22.0 | 176 | 0.5509 | 0.7196 |
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| 0.5308 | 23.0 | 184 | 0.5602 | 0.7570 |
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| 0.4595 | 24.0 | 192 | 0.4735 | 0.7850 |
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| 0.4553 | 25.0 | 200 | 0.4696 | 0.7664 |
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| 0.4553 | 26.0 | 208 | 0.5306 | 0.7850 |
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| 0.4004 | 27.0 | 216 | 0.4819 | 0.7944 |
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| 0.3954 | 28.0 | 224 | 0.4831 | 0.7944 |
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| 0.3521 | 29.0 | 232 | 0.4340 | 0.8037 |
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| 0.3436 | 30.0 | 240 | 0.4790 | 0.7757 |
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| 0.3436 | 31.0 | 248 | 0.4720 | 0.7757 |
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| 0.34 | 32.0 | 256 | 0.5283 | 0.7850 |
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| 0.2995 | 33.0 | 264 | 0.4383 | 0.7944 |
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| 0.2951 | 34.0 | 272 | 0.4740 | 0.7944 |
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| 0.3094 | 35.0 | 280 | 0.5863 | 0.7664 |
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| 0.3094 | 36.0 | 288 | 0.4483 | 0.7850 |
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| 0.2963 | 37.0 | 296 | 0.4759 | 0.7944 |
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| 0.3045 | 38.0 | 304 | 0.4469 | 0.7944 |
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| 0.2739 | 39.0 | 312 | 0.4517 | 0.7850 |
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| 0.2717 | 40.0 | 320 | 0.4654 | 0.7944 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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