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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-large-patch16_fold1
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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: 0.6581591094216671
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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-large-patch16_fold1
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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: 1.6175
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- Accuracy: 0.6582
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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: 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: 10
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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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| 1.0967 | 1.0 | 924 | 1.1282 | 0.6305 |
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| 0.9514 | 2.0 | 1848 | 1.0677 | 0.6335 |
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| 0.8134 | 3.0 | 2772 | 0.9657 | 0.6761 |
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| 0.5172 | 4.0 | 3696 | 1.0638 | 0.6641 |
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| 0.4644 | 5.0 | 4620 | 1.1745 | 0.6655 |
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| 0.3079 | 6.0 | 5544 | 1.2914 | 0.6601 |
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| 0.1569 | 7.0 | 6468 | 1.4210 | 0.6636 |
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| 0.1324 | 8.0 | 7392 | 1.5083 | 0.6603 |
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| 0.0833 | 9.0 | 8316 | 1.5875 | 0.6644 |
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| 0.1019 | 10.0 | 9240 | 1.6175 | 0.6582 |
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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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