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--- |
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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-large-patch16-224-finetuned-landscape-test |
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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: 0.909375 |
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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-large-patch16-224-finetuned-landscape-test |
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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: 0.3101 |
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- Accuracy: 0.9094 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 30 |
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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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| 1.3906 | 1.0 | 10 | 1.1521 | 0.4969 | |
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| 0.914 | 2.0 | 20 | 0.7812 | 0.6687 | |
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| 0.6704 | 3.0 | 30 | 0.5566 | 0.7688 | |
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| 0.4609 | 4.0 | 40 | 0.4363 | 0.8313 | |
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| 0.404 | 5.0 | 50 | 0.4807 | 0.8156 | |
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| 0.3948 | 6.0 | 60 | 0.4216 | 0.8531 | |
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| 0.3535 | 7.0 | 70 | 0.3281 | 0.8688 | |
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| 0.3107 | 8.0 | 80 | 0.2972 | 0.9 | |
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| 0.3086 | 9.0 | 90 | 0.3328 | 0.8812 | |
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| 0.2564 | 10.0 | 100 | 0.3517 | 0.8875 | |
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| 0.2654 | 11.0 | 110 | 0.3985 | 0.8594 | |
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| 0.2733 | 12.0 | 120 | 0.2870 | 0.9062 | |
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| 0.2511 | 13.0 | 130 | 0.4177 | 0.8875 | |
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| 0.2762 | 14.0 | 140 | 0.3579 | 0.8938 | |
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| 0.2188 | 15.0 | 150 | 0.3348 | 0.8906 | |
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| 0.2265 | 16.0 | 160 | 0.3046 | 0.9031 | |
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| 0.2054 | 17.0 | 170 | 0.3305 | 0.8969 | |
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| 0.1951 | 18.0 | 180 | 0.3576 | 0.8812 | |
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| 0.1762 | 19.0 | 190 | 0.3985 | 0.8812 | |
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| 0.2264 | 20.0 | 200 | 0.3711 | 0.9031 | |
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| 0.1958 | 21.0 | 210 | 0.3259 | 0.8875 | |
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| 0.1765 | 22.0 | 220 | 0.3804 | 0.8938 | |
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| 0.1859 | 23.0 | 230 | 0.3464 | 0.9 | |
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| 0.1915 | 24.0 | 240 | 0.3742 | 0.8906 | |
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| 0.1667 | 25.0 | 250 | 0.3200 | 0.9062 | |
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| 0.1744 | 26.0 | 260 | 0.3545 | 0.8938 | |
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| 0.1595 | 27.0 | 270 | 0.3101 | 0.9094 | |
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| 0.1793 | 28.0 | 280 | 0.3230 | 0.8969 | |
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| 0.1596 | 29.0 | 290 | 0.3268 | 0.9 | |
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| 0.169 | 30.0 | 300 | 0.3321 | 0.8969 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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