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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-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: results |
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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[80%:] |
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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: 0.0625 |
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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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# results |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-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: 4.5590 |
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- Accuracy: 0.0625 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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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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| 1.6612 | 1.0 | 40 | 3.9513 | 0.0 | |
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| 0.8129 | 2.0 | 80 | 3.9721 | 0.025 | |
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| 0.3799 | 3.0 | 120 | 4.3376 | 0.0125 | |
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| 0.0946 | 4.0 | 160 | 4.4142 | 0.0563 | |
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| 0.019 | 5.0 | 200 | 4.5590 | 0.0625 | |
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| 0.0062 | 6.0 | 240 | 4.9286 | 0.0437 | |
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| 0.0039 | 7.0 | 280 | 5.0577 | 0.0437 | |
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| 0.0028 | 8.0 | 320 | 5.1624 | 0.0437 | |
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| 0.0024 | 9.0 | 360 | 5.2316 | 0.0437 | |
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| 0.0023 | 10.0 | 400 | 5.2923 | 0.0437 | |
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| 0.0019 | 11.0 | 440 | 5.3317 | 0.0375 | |
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| 0.0017 | 12.0 | 480 | 5.3658 | 0.0375 | |
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| 0.0016 | 13.0 | 520 | 5.3915 | 0.0375 | |
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| 0.0016 | 14.0 | 560 | 5.4004 | 0.0375 | |
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| 0.0016 | 15.0 | 600 | 5.4022 | 0.0375 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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