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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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- image_folder |
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metrics: |
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- accuracy |
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model-index: |
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- name: hf_images_model1 |
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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: image_folder |
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type: image_folder |
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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: 0.9178265524625268 |
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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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# hf_images_model1 |
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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 image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2058 |
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- Accuracy: 0.9178 |
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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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- 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: 3 |
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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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| 0.7057 | 0.04 | 10 | 0.7027 | 0.4644 | |
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| 0.6808 | 0.09 | 20 | 0.6615 | 0.6590 | |
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| 0.6278 | 0.13 | 30 | 0.5969 | 0.7441 | |
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| 0.5674 | 0.17 | 40 | 0.5134 | 0.8183 | |
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| 0.4761 | 0.21 | 50 | 0.4146 | 0.875 | |
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| 0.3777 | 0.26 | 60 | 0.3362 | 0.8796 | |
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| 0.303 | 0.3 | 70 | 0.2906 | 0.8854 | |
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| 0.2385 | 0.34 | 80 | 0.2694 | 0.8937 | |
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| 0.2452 | 0.39 | 90 | 0.2515 | 0.9012 | |
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| 0.2771 | 0.43 | 100 | 0.2441 | 0.9050 | |
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| 0.2332 | 0.47 | 110 | 0.2510 | 0.8975 | |
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| 0.2495 | 0.51 | 120 | 0.2398 | 0.9052 | |
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| 0.2611 | 0.56 | 130 | 0.2384 | 0.9063 | |
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| 0.2292 | 0.6 | 140 | 0.2931 | 0.8865 | |
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| 0.2518 | 0.64 | 150 | 0.2537 | 0.8994 | |
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| 0.211 | 0.69 | 160 | 0.2619 | 0.8953 | |
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| 0.2514 | 0.73 | 170 | 0.2236 | 0.9090 | |
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| 0.2272 | 0.77 | 180 | 0.2254 | 0.9085 | |
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| 0.2263 | 0.81 | 190 | 0.2141 | 0.9181 | |
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| 0.2524 | 0.86 | 200 | 0.2038 | 0.9194 | |
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| 0.2024 | 0.9 | 210 | 0.2038 | 0.9165 | |
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| 0.2355 | 0.94 | 220 | 0.2215 | 0.9103 | |
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| 0.2431 | 0.99 | 230 | 0.2116 | 0.9178 | |
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| 0.1921 | 1.03 | 240 | 0.2105 | 0.9111 | |
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| 0.1845 | 1.07 | 250 | 0.2107 | 0.9117 | |
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| 0.1838 | 1.11 | 260 | 0.2070 | 0.9119 | |
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| 0.1824 | 1.16 | 270 | 0.2110 | 0.9130 | |
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| 0.1706 | 1.2 | 280 | 0.2177 | 0.9154 | |
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| 0.1826 | 1.24 | 290 | 0.2058 | 0.9160 | |
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| 0.1816 | 1.28 | 300 | 0.2081 | 0.9176 | |
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| 0.1901 | 1.33 | 310 | 0.2187 | 0.9149 | |
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| 0.2112 | 1.37 | 320 | 0.2107 | 0.9181 | |
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| 0.22 | 1.41 | 330 | 0.2065 | 0.9173 | |
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| 0.2105 | 1.46 | 340 | 0.2090 | 0.9170 | |
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| 0.2016 | 1.5 | 350 | 0.2044 | 0.9141 | |
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| 0.2055 | 1.54 | 360 | 0.2029 | 0.9173 | |
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| 0.1507 | 1.58 | 370 | 0.2103 | 0.9192 | |
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| 0.1705 | 1.63 | 380 | 0.1960 | 0.9184 | |
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| 0.1605 | 1.67 | 390 | 0.2070 | 0.9154 | |
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| 0.2011 | 1.71 | 400 | 0.2096 | 0.9160 | |
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| 0.1832 | 1.76 | 410 | 0.2023 | 0.9176 | |
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| 0.1756 | 1.8 | 420 | 0.2005 | 0.9189 | |
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| 0.1874 | 1.84 | 430 | 0.2050 | 0.9135 | |
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| 0.1497 | 1.88 | 440 | 0.1936 | 0.9240 | |
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| 0.1891 | 1.93 | 450 | 0.1991 | 0.9208 | |
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| 0.1595 | 1.97 | 460 | 0.2014 | 0.9194 | |
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| 0.2028 | 2.01 | 470 | 0.1994 | 0.9184 | |
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| 0.1794 | 2.06 | 480 | 0.2068 | 0.9146 | |
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| 0.1404 | 2.1 | 490 | 0.2046 | 0.9181 | |
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| 0.1615 | 2.14 | 500 | 0.1955 | 0.9243 | |
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| 0.1555 | 2.18 | 510 | 0.2027 | 0.9202 | |
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| 0.151 | 2.23 | 520 | 0.1893 | 0.9261 | |
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| 0.1676 | 2.27 | 530 | 0.2046 | 0.9192 | |
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| 0.1744 | 2.31 | 540 | 0.1967 | 0.9218 | |
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| 0.1644 | 2.36 | 550 | 0.1970 | 0.9226 | |
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| 0.2048 | 2.4 | 560 | 0.1930 | 0.9243 | |
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| 0.1649 | 2.44 | 570 | 0.1986 | 0.9218 | |
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| 0.1435 | 2.48 | 580 | 0.1956 | 0.9213 | |
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| 0.1598 | 2.53 | 590 | 0.1986 | 0.9197 | |
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| 0.1513 | 2.57 | 600 | 0.2020 | 0.9173 | |
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| 0.1769 | 2.61 | 610 | 0.2005 | 0.9170 | |
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| 0.1488 | 2.66 | 620 | 0.2033 | 0.9197 | |
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| 0.1636 | 2.7 | 630 | 0.1964 | 0.9216 | |
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| 0.1583 | 2.74 | 640 | 0.1985 | 0.9189 | |
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| 0.1294 | 2.78 | 650 | 0.2109 | 0.9151 | |
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| 0.1585 | 2.83 | 660 | 0.2000 | 0.9186 | |
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| 0.1531 | 2.87 | 670 | 0.2078 | 0.9178 | |
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| 0.1294 | 2.91 | 680 | 0.1891 | 0.9272 | |
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| 0.1612 | 2.96 | 690 | 0.2058 | 0.9178 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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