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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: output_dir |
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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: 0.6 |
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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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# output_dir |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2976 |
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- Accuracy: 0.6 |
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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: 7e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: reduce_lr_on_plateau |
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- num_epochs: 77 |
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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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| No log | 0.8 | 2 | 2.0706 | 0.15 | |
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| No log | 2.0 | 5 | 2.0309 | 0.2313 | |
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| No log | 2.8 | 7 | 1.9846 | 0.2562 | |
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| 1.9868 | 4.0 | 10 | 1.8915 | 0.4062 | |
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| 1.9868 | 4.8 | 12 | 1.8529 | 0.3125 | |
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| 1.9868 | 6.0 | 15 | 1.7422 | 0.4125 | |
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| 1.9868 | 6.8 | 17 | 1.6761 | 0.4313 | |
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| 1.6815 | 8.0 | 20 | 1.6310 | 0.4562 | |
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| 1.6815 | 8.8 | 22 | 1.5900 | 0.45 | |
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| 1.6815 | 10.0 | 25 | 1.5402 | 0.4313 | |
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| 1.6815 | 10.8 | 27 | 1.5018 | 0.5 | |
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| 1.4233 | 12.0 | 30 | 1.4620 | 0.4875 | |
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| 1.4233 | 12.8 | 32 | 1.4286 | 0.5062 | |
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| 1.4233 | 14.0 | 35 | 1.4045 | 0.5125 | |
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| 1.4233 | 14.8 | 37 | 1.3860 | 0.5312 | |
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| 1.2127 | 16.0 | 40 | 1.3571 | 0.5 | |
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| 1.2127 | 16.8 | 42 | 1.3293 | 0.5375 | |
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| 1.2127 | 18.0 | 45 | 1.3742 | 0.4813 | |
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| 1.2127 | 18.8 | 47 | 1.3151 | 0.5437 | |
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| 1.0075 | 20.0 | 50 | 1.3053 | 0.5312 | |
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| 1.0075 | 20.8 | 52 | 1.3266 | 0.5375 | |
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| 1.0075 | 22.0 | 55 | 1.2964 | 0.5312 | |
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| 1.0075 | 22.8 | 57 | 1.2278 | 0.5875 | |
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| 0.8232 | 24.0 | 60 | 1.2501 | 0.5563 | |
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| 0.8232 | 24.8 | 62 | 1.2330 | 0.575 | |
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| 0.8232 | 26.0 | 65 | 1.2198 | 0.5625 | |
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| 0.8232 | 26.8 | 67 | 1.2071 | 0.5875 | |
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| 0.6738 | 28.0 | 70 | 1.2643 | 0.5875 | |
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| 0.6738 | 28.8 | 72 | 1.2594 | 0.5563 | |
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| 0.6738 | 30.0 | 75 | 1.2263 | 0.5312 | |
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| 0.6738 | 30.8 | 77 | 1.3218 | 0.5188 | |
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| 0.5715 | 32.0 | 80 | 1.2593 | 0.5312 | |
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| 0.5715 | 32.8 | 82 | 1.2214 | 0.5625 | |
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| 0.5715 | 34.0 | 85 | 1.3060 | 0.55 | |
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| 0.5715 | 34.8 | 87 | 1.2727 | 0.5563 | |
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| 0.4523 | 36.0 | 90 | 1.2749 | 0.5375 | |
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| 0.4523 | 36.8 | 92 | 1.3570 | 0.5437 | |
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| 0.4523 | 38.0 | 95 | 1.2815 | 0.5687 | |
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| 0.4523 | 38.8 | 97 | 1.2233 | 0.6062 | |
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| 0.3971 | 40.0 | 100 | 1.2097 | 0.6 | |
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| 0.3971 | 40.8 | 102 | 1.2881 | 0.5813 | |
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| 0.3971 | 42.0 | 105 | 1.2400 | 0.575 | |
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| 0.3971 | 42.8 | 107 | 1.3140 | 0.5375 | |
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| 0.3616 | 44.0 | 110 | 1.1525 | 0.6125 | |
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| 0.3616 | 44.8 | 112 | 1.2725 | 0.5938 | |
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| 0.3616 | 46.0 | 115 | 1.2634 | 0.5813 | |
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| 0.3616 | 46.8 | 117 | 1.2299 | 0.6 | |
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| 0.338 | 48.0 | 120 | 1.3408 | 0.5375 | |
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| 0.338 | 48.8 | 122 | 1.1931 | 0.5938 | |
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| 0.338 | 50.0 | 125 | 1.2806 | 0.5938 | |
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| 0.338 | 50.8 | 127 | 1.2410 | 0.575 | |
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| 0.3445 | 52.0 | 130 | 1.2901 | 0.5813 | |
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| 0.3445 | 52.8 | 132 | 1.2504 | 0.6062 | |
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| 0.3445 | 54.0 | 135 | 1.1614 | 0.5875 | |
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| 0.3445 | 54.8 | 137 | 1.2247 | 0.6062 | |
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| 0.3299 | 56.0 | 140 | 1.2591 | 0.5625 | |
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| 0.3299 | 56.8 | 142 | 1.2629 | 0.5687 | |
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| 0.3299 | 58.0 | 145 | 1.2369 | 0.5938 | |
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| 0.3299 | 58.8 | 147 | 1.2771 | 0.575 | |
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| 0.3292 | 60.0 | 150 | 1.3284 | 0.5875 | |
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| 0.3292 | 60.8 | 152 | 1.2550 | 0.5625 | |
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| 0.3292 | 61.6 | 154 | 1.3047 | 0.55 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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