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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-RD
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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: 0.8672727272727273
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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-RD
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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: 0.3771
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- Accuracy: 0.8673
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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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| 1.4986 | 0.99 | 40 | 1.4512 | 0.4945 |
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| 1.0553 | 1.99 | 80 | 0.9355 | 0.7473 |
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| 0.7972 | 2.98 | 120 | 0.7250 | 0.7436 |
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| 0.7156 | 4.0 | 161 | 0.5845 | 0.7582 |
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| 0.6723 | 4.99 | 201 | 0.5509 | 0.8036 |
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| 0.5942 | 5.99 | 241 | 0.5018 | 0.8218 |
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| 0.6223 | 6.98 | 281 | 0.4993 | 0.8218 |
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| 0.5731 | 8.0 | 322 | 0.4590 | 0.8291 |
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| 0.5583 | 8.99 | 362 | 0.4878 | 0.8 |
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| 0.5784 | 9.99 | 402 | 0.4485 | 0.8455 |
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| 0.4968 | 10.98 | 442 | 0.4305 | 0.8345 |
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| 0.5324 | 12.0 | 483 | 0.4737 | 0.8345 |
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| 0.4629 | 12.99 | 523 | 0.4253 | 0.8436 |
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| 0.4398 | 13.99 | 563 | 0.4184 | 0.8473 |
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| 0.4575 | 14.98 | 603 | 0.3929 | 0.8564 |
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| 0.4554 | 16.0 | 644 | 0.4282 | 0.8491 |
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| 0.4646 | 16.99 | 684 | 0.4363 | 0.8236 |
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| 0.4535 | 17.99 | 724 | 0.4337 | 0.8455 |
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| 0.3823 | 18.98 | 764 | 0.3771 | 0.8673 |
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| 0.4584 | 20.0 | 805 | 0.3966 | 0.8564 |
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| 0.4103 | 20.99 | 845 | 0.4001 | 0.8491 |
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| 0.3659 | 21.99 | 885 | 0.3948 | 0.8582 |
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| 0.3241 | 22.98 | 925 | 0.4007 | 0.8582 |
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| 0.3575 | 24.0 | 966 | 0.4328 | 0.8327 |
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| 0.3411 | 24.99 | 1006 | 0.3990 | 0.8564 |
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| 0.3829 | 25.99 | 1046 | 0.4011 | 0.8636 |
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| 0.2855 | 26.98 | 1086 | 0.3859 | 0.8655 |
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| 0.254 | 28.0 | 1127 | 0.4196 | 0.8673 |
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| 0.2937 | 28.99 | 1167 | 0.4340 | 0.8618 |
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| 0.258 | 29.99 | 1207 | 0.4387 | 0.8509 |
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| 0.2735 | 30.98 | 1247 | 0.4097 | 0.8655 |
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| 0.2674 | 32.0 | 1288 | 0.4183 | 0.8527 |
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| 0.2547 | 32.99 | 1328 | 0.4217 | 0.8636 |
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| 0.2109 | 33.99 | 1368 | 0.4240 | 0.8527 |
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| 0.2248 | 34.98 | 1408 | 0.4250 | 0.86 |
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| 0.2397 | 36.0 | 1449 | 0.4431 | 0.8582 |
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| 0.1823 | 36.99 | 1489 | 0.4442 | 0.8582 |
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| 0.1834 | 37.99 | 1529 | 0.4362 | 0.8618 |
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| 0.1864 | 38.98 | 1569 | 0.4338 | 0.8545 |
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| 0.1779 | 39.75 | 1600 | 0.4332 | 0.8582 |
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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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