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---
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license: apache-2.0
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base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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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: Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_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: 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: 0.6552845528455284
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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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# Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold4
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.1034
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- Accuracy: 0.6553
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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: 0.0001
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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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- 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: 20
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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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| 1.1966 | 1.0 | 923 | 1.1276 | 0.5995 |
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| 1.0326 | 2.0 | 1846 | 1.0374 | 0.6360 |
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| 0.6666 | 3.0 | 2769 | 1.0904 | 0.6415 |
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| 0.4288 | 4.0 | 3692 | 1.2437 | 0.6474 |
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| 0.2209 | 5.0 | 4615 | 1.4346 | 0.6404 |
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| 0.1143 | 6.0 | 5538 | 1.6952 | 0.6442 |
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| 0.1733 | 7.0 | 6461 | 1.9268 | 0.6547 |
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| 0.0409 | 8.0 | 7384 | 2.2016 | 0.6518 |
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| 0.0999 | 9.0 | 8307 | 2.4623 | 0.6485 |
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| 0.0104 | 10.0 | 9230 | 2.6094 | 0.6534 |
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| 0.0424 | 11.0 | 10153 | 2.7340 | 0.6558 |
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| 0.0463 | 12.0 | 11076 | 2.8098 | 0.6599 |
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| 0.0005 | 13.0 | 11999 | 2.9333 | 0.6553 |
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| 0.0144 | 14.0 | 12922 | 2.9705 | 0.6531 |
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| 0.0002 | 15.0 | 13845 | 3.0020 | 0.6566 |
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| 0.0157 | 16.0 | 14768 | 3.0642 | 0.6588 |
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| 0.0005 | 17.0 | 15691 | 3.0529 | 0.6575 |
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| 0.0029 | 18.0 | 16614 | 3.0952 | 0.6558 |
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| 0.0024 | 19.0 | 17537 | 3.0982 | 0.6572 |
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| 0.0001 | 20.0 | 18460 | 3.1034 | 0.6553 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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