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ryan03302024

Image Classification
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TensorBoard
Safetensors
vit
Generated from Trainer
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README.md CHANGED
@@ -14,6 +14,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # ryan03302024
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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 None dataset.
 
 
 
 
 
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  ## Model description
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@@ -43,6 +48,91 @@ The following hyperparameters were used during training:
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  ### Training results
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  ### Framework versions
 
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  # ryan03302024
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2520
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+ - Ordinal Mae: 0.3265
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+ - Ordinal Accuracy: 0.7167
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+ - Na Accuracy: 0.8144
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Ordinal Mae | Ordinal Accuracy | Na Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
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+ | 0.3617 | 0.04 | 100 | 0.3133 | 0.8466 | 0.4174 | 0.8763 |
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+ | 0.2891 | 0.07 | 200 | 0.3022 | 0.7739 | 0.5045 | 0.6993 |
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+ | 0.3163 | 0.11 | 300 | 0.2615 | 0.6167 | 0.5597 | 0.7904 |
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+ | 0.2781 | 0.14 | 400 | 0.2598 | 0.5433 | 0.5936 | 0.8299 |
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+ | 0.2731 | 0.18 | 500 | 0.2613 | 0.5651 | 0.5566 | 0.8454 |
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+ | 0.2926 | 0.22 | 600 | 0.2734 | 0.5305 | 0.5494 | 0.9089 |
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+ | 0.2686 | 0.25 | 700 | 0.2362 | 0.4853 | 0.6250 | 0.7887 |
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+ | 0.2715 | 0.29 | 800 | 0.2454 | 0.4914 | 0.6255 | 0.7715 |
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+ | 0.2459 | 0.32 | 900 | 0.2452 | 0.4763 | 0.6072 | 0.7801 |
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+ | 0.2033 | 0.36 | 1000 | 0.2365 | 0.4967 | 0.6106 | 0.7663 |
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+ | 0.2234 | 0.4 | 1100 | 0.2299 | 0.4947 | 0.6180 | 0.8677 |
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+ | 0.2035 | 0.43 | 1200 | 0.2314 | 0.4744 | 0.6309 | 0.7835 |
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+ | 0.2277 | 0.47 | 1300 | 0.2389 | 0.4649 | 0.6435 | 0.7302 |
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+ | 0.2535 | 0.5 | 1400 | 0.2259 | 0.4509 | 0.6021 | 0.8247 |
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+ | 0.2209 | 0.54 | 1500 | 0.2369 | 0.4507 | 0.6363 | 0.7577 |
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+ | 0.2007 | 0.58 | 1600 | 0.2161 | 0.4272 | 0.6540 | 0.8316 |
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+ | 0.2013 | 0.61 | 1700 | 0.2433 | 0.4326 | 0.6129 | 0.7732 |
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+ | 0.1999 | 0.65 | 1800 | 0.2227 | 0.4460 | 0.6553 | 0.8247 |
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+ | 0.2157 | 0.69 | 1900 | 0.2134 | 0.4728 | 0.6363 | 0.8162 |
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+ | 0.2154 | 0.72 | 2000 | 0.2239 | 0.4734 | 0.5787 | 0.8574 |
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+ | 0.2169 | 0.76 | 2100 | 0.2394 | 0.4392 | 0.6255 | 0.8849 |
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+ | 0.2719 | 0.79 | 2200 | 0.2283 | 0.4324 | 0.6229 | 0.8780 |
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+ | 0.2244 | 0.83 | 2300 | 0.2140 | 0.4483 | 0.6314 | 0.8729 |
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+ | 0.2072 | 0.87 | 2400 | 0.2198 | 0.4330 | 0.6440 | 0.8213 |
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+ | 0.1754 | 0.9 | 2500 | 0.2099 | 0.4198 | 0.6712 | 0.8419 |
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+ | 0.1773 | 0.94 | 2600 | 0.2053 | 0.4105 | 0.6586 | 0.8643 |
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+ | 0.2378 | 0.97 | 2700 | 0.2044 | 0.4324 | 0.6648 | 0.8333 |
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+ | 0.1295 | 1.01 | 2800 | 0.2044 | 0.4016 | 0.6843 | 0.8247 |
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+ | 0.1126 | 1.05 | 2900 | 0.2302 | 0.4025 | 0.6805 | 0.7577 |
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+ | 0.1262 | 1.08 | 3000 | 0.2205 | 0.4017 | 0.6517 | 0.8093 |
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+ | 0.1104 | 1.12 | 3100 | 0.2117 | 0.3931 | 0.6779 | 0.8454 |
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+ | 0.1657 | 1.15 | 3200 | 0.2174 | 0.3890 | 0.6666 | 0.8591 |
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+ | 0.1186 | 1.19 | 3300 | 0.2299 | 0.4013 | 0.6622 | 0.8058 |
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+ | 0.1304 | 1.23 | 3400 | 0.2176 | 0.3801 | 0.6902 | 0.8110 |
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+ | 0.1081 | 1.26 | 3500 | 0.2330 | 0.3867 | 0.6643 | 0.8316 |
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+ | 0.1281 | 1.3 | 3600 | 0.2320 | 0.3954 | 0.6902 | 0.7680 |
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+ | 0.1192 | 1.33 | 3700 | 0.2312 | 0.4109 | 0.6769 | 0.7990 |
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+ | 0.1029 | 1.37 | 3800 | 0.2195 | 0.3870 | 0.6820 | 0.8024 |
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+ | 0.1159 | 1.41 | 3900 | 0.2200 | 0.3860 | 0.6812 | 0.7904 |
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+ | 0.1159 | 1.44 | 4000 | 0.2159 | 0.3712 | 0.6982 | 0.7990 |
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+ | 0.107 | 1.48 | 4100 | 0.2262 | 0.3757 | 0.6905 | 0.8213 |
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+ | 0.1262 | 1.51 | 4200 | 0.2291 | 0.3841 | 0.6835 | 0.8247 |
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+ | 0.1437 | 1.55 | 4300 | 0.2311 | 0.3751 | 0.6923 | 0.8007 |
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+ | 0.0916 | 1.59 | 4400 | 0.2343 | 0.3743 | 0.6792 | 0.8660 |
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+ | 0.1266 | 1.62 | 4500 | 0.2251 | 0.3724 | 0.6861 | 0.8505 |
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+ | 0.1185 | 1.66 | 4600 | 0.2242 | 0.3666 | 0.6902 | 0.8265 |
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+ | 0.1037 | 1.69 | 4700 | 0.2219 | 0.3700 | 0.6846 | 0.8522 |
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+ | 0.1264 | 1.73 | 4800 | 0.2211 | 0.3677 | 0.6892 | 0.8351 |
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+ | 0.1404 | 1.77 | 4900 | 0.2206 | 0.3718 | 0.6946 | 0.7938 |
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+ | 0.1238 | 1.8 | 5000 | 0.2098 | 0.3723 | 0.6948 | 0.8265 |
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+ | 0.0868 | 1.84 | 5100 | 0.2089 | 0.3574 | 0.7025 | 0.8144 |
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+ | 0.0828 | 1.88 | 5200 | 0.2204 | 0.3680 | 0.7031 | 0.7818 |
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+ | 0.0986 | 1.91 | 5300 | 0.2126 | 0.3543 | 0.6982 | 0.8127 |
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+ | 0.0869 | 1.95 | 5400 | 0.2247 | 0.3532 | 0.7108 | 0.8076 |
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+ | 0.1006 | 1.98 | 5500 | 0.2268 | 0.3637 | 0.7028 | 0.8162 |
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+ | 0.0639 | 2.02 | 5600 | 0.2252 | 0.3479 | 0.7069 | 0.8110 |
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+ | 0.0569 | 2.06 | 5700 | 0.2315 | 0.3399 | 0.7167 | 0.8076 |
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+ | 0.0626 | 2.09 | 5800 | 0.2304 | 0.3481 | 0.7028 | 0.8127 |
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+ | 0.0502 | 2.13 | 5900 | 0.2381 | 0.3624 | 0.6954 | 0.8093 |
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+ | 0.0541 | 2.16 | 6000 | 0.2298 | 0.3405 | 0.7159 | 0.8110 |
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+ | 0.0671 | 2.2 | 6100 | 0.2432 | 0.3529 | 0.7031 | 0.7990 |
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+ | 0.0672 | 2.24 | 6200 | 0.2431 | 0.3361 | 0.7195 | 0.7715 |
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+ | 0.0446 | 2.27 | 6300 | 0.2447 | 0.3401 | 0.7141 | 0.7938 |
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+ | 0.0424 | 2.31 | 6400 | 0.2426 | 0.3485 | 0.7018 | 0.8162 |
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+ | 0.0386 | 2.34 | 6500 | 0.2488 | 0.3387 | 0.7123 | 0.8127 |
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+ | 0.0736 | 2.38 | 6600 | 0.2454 | 0.3382 | 0.7054 | 0.8316 |
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+ | 0.0421 | 2.42 | 6700 | 0.2513 | 0.3394 | 0.7120 | 0.8316 |
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+ | 0.0607 | 2.45 | 6800 | 0.2546 | 0.3370 | 0.7092 | 0.8265 |
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+ | 0.0517 | 2.49 | 6900 | 0.2594 | 0.3376 | 0.7082 | 0.8299 |
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+ | 0.062 | 2.52 | 7000 | 0.2533 | 0.3369 | 0.7105 | 0.8110 |
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+ | 0.0664 | 2.56 | 7100 | 0.2534 | 0.3329 | 0.7185 | 0.8024 |
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+ | 0.0389 | 2.6 | 7200 | 0.2470 | 0.3288 | 0.7259 | 0.8093 |
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+ | 0.0671 | 2.63 | 7300 | 0.2516 | 0.3294 | 0.7159 | 0.8041 |
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+ | 0.0416 | 2.67 | 7400 | 0.2507 | 0.3307 | 0.7133 | 0.8058 |
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+ | 0.0541 | 2.7 | 7500 | 0.2529 | 0.3355 | 0.7110 | 0.8058 |
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+ | 0.0374 | 2.74 | 7600 | 0.2530 | 0.3315 | 0.7149 | 0.8110 |
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+ | 0.04 | 2.78 | 7700 | 0.2520 | 0.3290 | 0.7167 | 0.8076 |
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+ | 0.0507 | 2.81 | 7800 | 0.2555 | 0.3297 | 0.7105 | 0.8127 |
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+ | 0.0379 | 2.85 | 7900 | 0.2531 | 0.3274 | 0.7162 | 0.8127 |
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+ | 0.0736 | 2.88 | 8000 | 0.2526 | 0.3279 | 0.7164 | 0.8196 |
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+ | 0.0589 | 2.92 | 8100 | 0.2522 | 0.3267 | 0.7144 | 0.8162 |
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+ | 0.0449 | 2.96 | 8200 | 0.2521 | 0.3272 | 0.7149 | 0.8162 |
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+ | 0.0498 | 2.99 | 8300 | 0.2520 | 0.3265 | 0.7167 | 0.8144 |
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  ### Framework versions
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