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--- |
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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: vit-base-patch16-224-13_model |
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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: 0.835 |
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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-base-patch16-224-13_model |
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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: 0.5185 |
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- Accuracy: 0.835 |
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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: 0.0002 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 9 |
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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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| 1.7535 | 0.9787 | 23 | 1.3773 | 0.545 | |
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| 0.9606 | 2.0 | 47 | 1.1264 | 0.625 | |
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| 0.5199 | 2.9787 | 70 | 0.7703 | 0.705 | |
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| 0.3037 | 4.0 | 94 | 0.6922 | 0.745 | |
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| 0.1607 | 4.9787 | 117 | 0.5718 | 0.81 | |
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| 0.148 | 6.0 | 141 | 0.5436 | 0.82 | |
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| 0.1238 | 6.9787 | 164 | 0.5454 | 0.805 | |
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| 0.0889 | 8.0 | 188 | 0.5023 | 0.84 | |
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| 0.0745 | 8.8085 | 207 | 0.5185 | 0.835 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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