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README.md
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---
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license: apache-2.0
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base_model: microsoft/cvt-13
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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: cvt-13
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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: 0.9886363636363636
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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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# cvt-13
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This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0361
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- Accuracy: 0.9886
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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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: 15
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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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| 0.4048 | 1.0 | 327 | 0.2161 | 0.9156 |
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| 0.33 | 2.0 | 654 | 0.1320 | 0.9501 |
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| 0.3147 | 3.0 | 981 | 0.1060 | 0.9612 |
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| 0.2213 | 4.0 | 1309 | 0.0820 | 0.9742 |
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| 0.3256 | 5.0 | 1636 | 0.0717 | 0.9750 |
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| 0.3207 | 6.0 | 1963 | 0.1062 | 0.9626 |
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| 0.2273 | 7.0 | 2290 | 0.0535 | 0.9797 |
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| 0.2066 | 8.0 | 2618 | 0.0566 | 0.9817 |
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| 0.2162 | 9.0 | 2945 | 0.0459 | 0.9828 |
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| 0.2296 | 10.0 | 3272 | 0.0444 | 0.9851 |
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| 0.187 | 11.0 | 3599 | 0.0348 | 0.9882 |
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| 0.2208 | 12.0 | 3927 | 0.0505 | 0.9848 |
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| 0.1855 | 13.0 | 4254 | 0.0371 | 0.9869 |
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| 0.1875 | 14.0 | 4581 | 0.0384 | 0.9880 |
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| 0.202 | 14.99 | 4905 | 0.0361 | 0.9886 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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