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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-large-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: vit |
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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: 0.9985885673959068 |
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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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# vit |
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This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0048 |
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- Accuracy: 0.9986 |
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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: 2e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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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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| 0.2323 | 1.0 | 1595 | 0.0450 | 0.9859 | |
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| 0.095 | 2.0 | 3190 | 0.0332 | 0.9889 | |
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| 0.0648 | 3.0 | 4785 | 0.0256 | 0.9922 | |
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| 0.0568 | 4.0 | 6380 | 0.0145 | 0.9958 | |
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| 0.0493 | 5.0 | 7975 | 0.0248 | 0.9915 | |
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| 0.042 | 6.0 | 9570 | 0.0195 | 0.9939 | |
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| 0.0383 | 7.0 | 11165 | 0.0087 | 0.9969 | |
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| 0.0345 | 8.0 | 12760 | 0.0143 | 0.9960 | |
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| 0.0285 | 9.0 | 14355 | 0.0115 | 0.9972 | |
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| 0.0257 | 10.0 | 15950 | 0.0131 | 0.9965 | |
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| 0.0248 | 11.0 | 17545 | 0.0068 | 0.9979 | |
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| 0.0235 | 12.0 | 19140 | 0.0065 | 0.9979 | |
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| 0.0201 | 13.0 | 20735 | 0.0056 | 0.9976 | |
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| 0.0161 | 14.0 | 22330 | 0.0033 | 0.9988 | |
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| 0.017 | 15.0 | 23925 | 0.0041 | 0.9988 | |
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| 0.0144 | 16.0 | 25520 | 0.0032 | 0.9993 | |
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| 0.0121 | 17.0 | 27115 | 0.0055 | 0.9979 | |
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| 0.0105 | 18.0 | 28710 | 0.0052 | 0.9984 | |
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| 0.0103 | 19.0 | 30305 | 0.0054 | 0.9984 | |
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| 0.0092 | 20.0 | 31900 | 0.0048 | 0.9986 | |
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### Framework versions |
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- Transformers 4.53.0.dev0 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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