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chickens

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detr
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End of training

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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1949
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  ## Model description
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@@ -41,132 +41,75 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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- - num_epochs: 120
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 12 | 1.3837 |
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- | No log | 2.0 | 24 | 0.9192 |
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- | 1.2199 | 3.0 | 36 | 0.9478 |
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- | 1.2199 | 4.0 | 48 | 0.8188 |
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- | 0.9301 | 5.0 | 60 | 0.8648 |
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- | 0.9301 | 6.0 | 72 | 0.7913 |
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- | 0.9301 | 7.0 | 84 | 0.8269 |
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- | 0.834 | 8.0 | 96 | 0.7546 |
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- | 0.834 | 9.0 | 108 | 0.7128 |
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- | 0.7676 | 10.0 | 120 | 0.6706 |
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- | 0.7676 | 11.0 | 132 | 0.6042 |
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- | 0.7676 | 12.0 | 144 | 0.5586 |
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- | 0.6807 | 13.0 | 156 | 0.5129 |
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- | 0.6807 | 14.0 | 168 | 0.4815 |
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- | 0.5846 | 15.0 | 180 | 0.4724 |
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- | 0.5846 | 16.0 | 192 | 0.4970 |
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- | 0.5846 | 17.0 | 204 | 0.4900 |
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- | 0.5437 | 18.0 | 216 | 0.4985 |
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- | 0.5437 | 19.0 | 228 | 0.6295 |
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- | 0.5232 | 20.0 | 240 | 0.5023 |
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- | 0.5232 | 21.0 | 252 | 0.4312 |
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- | 0.5232 | 22.0 | 264 | 0.4583 |
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- | 0.5147 | 23.0 | 276 | 0.4499 |
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- | 0.5147 | 24.0 | 288 | 0.3438 |
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- | 0.4613 | 25.0 | 300 | 0.3953 |
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- | 0.4613 | 26.0 | 312 | 0.3916 |
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- | 0.4613 | 27.0 | 324 | 0.4285 |
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- | 0.4288 | 28.0 | 336 | 0.3532 |
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- | 0.4288 | 29.0 | 348 | 0.3513 |
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- | 0.4251 | 30.0 | 360 | 0.3761 |
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- | 0.4251 | 31.0 | 372 | 0.3183 |
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- | 0.4251 | 32.0 | 384 | 0.3419 |
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- | 0.3963 | 33.0 | 396 | 0.3186 |
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- | 0.3963 | 34.0 | 408 | 0.2799 |
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- | 0.3684 | 35.0 | 420 | 0.3688 |
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- | 0.3684 | 36.0 | 432 | 0.4035 |
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- | 0.3684 | 37.0 | 444 | 0.3491 |
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- | 0.4062 | 38.0 | 456 | 0.3147 |
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- | 0.4062 | 39.0 | 468 | 0.3333 |
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- | 0.3745 | 40.0 | 480 | 0.2822 |
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- | 0.3745 | 41.0 | 492 | 0.2734 |
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- | 0.3745 | 42.0 | 504 | 0.2816 |
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- | 0.3461 | 43.0 | 516 | 0.3289 |
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- | 0.3461 | 44.0 | 528 | 0.3538 |
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- | 0.3707 | 45.0 | 540 | 0.2969 |
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- | 0.3707 | 46.0 | 552 | 0.3335 |
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- | 0.3707 | 47.0 | 564 | 0.3201 |
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- | 0.3906 | 48.0 | 576 | 0.3262 |
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- | 0.3906 | 49.0 | 588 | 0.3213 |
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- | 0.3622 | 50.0 | 600 | 0.2825 |
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- | 0.3622 | 51.0 | 612 | 0.3111 |
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- | 0.3622 | 52.0 | 624 | 0.2814 |
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- | 0.336 | 53.0 | 636 | 0.3242 |
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- | 0.336 | 54.0 | 648 | 0.2615 |
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- | 0.3326 | 55.0 | 660 | 0.3107 |
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- | 0.3326 | 56.0 | 672 | 0.2904 |
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- | 0.3326 | 57.0 | 684 | 0.2967 |
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- | 0.3407 | 58.0 | 696 | 0.2818 |
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- | 0.3407 | 59.0 | 708 | 0.2759 |
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- | 0.3467 | 60.0 | 720 | 0.2862 |
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- | 0.3467 | 61.0 | 732 | 0.3529 |
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- | 0.3467 | 62.0 | 744 | 0.3559 |
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- | 0.354 | 63.0 | 756 | 0.2403 |
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- | 0.354 | 64.0 | 768 | 0.2815 |
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- | 0.3237 | 65.0 | 780 | 0.2819 |
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- | 0.3237 | 66.0 | 792 | 0.2476 |
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- | 0.3237 | 67.0 | 804 | 0.3193 |
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- | 0.3182 | 68.0 | 816 | 0.2444 |
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- | 0.3182 | 69.0 | 828 | 0.2510 |
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- | 0.3151 | 70.0 | 840 | 0.2951 |
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- | 0.3151 | 71.0 | 852 | 0.2389 |
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- | 0.3151 | 72.0 | 864 | 0.2657 |
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- | 0.3173 | 73.0 | 876 | 0.2783 |
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- | 0.3173 | 74.0 | 888 | 0.2791 |
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- | 0.3283 | 75.0 | 900 | 0.2445 |
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- | 0.3283 | 76.0 | 912 | 0.2507 |
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- | 0.3283 | 77.0 | 924 | 0.2778 |
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- | 0.3041 | 78.0 | 936 | 0.2471 |
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- | 0.3041 | 79.0 | 948 | 0.2219 |
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- | 0.2925 | 80.0 | 960 | 0.2767 |
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- | 0.2925 | 81.0 | 972 | 0.3046 |
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- | 0.2925 | 82.0 | 984 | 0.2837 |
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- | 0.3112 | 83.0 | 996 | 0.2710 |
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- | 0.3112 | 84.0 | 1008 | 0.2399 |
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- | 0.282 | 85.0 | 1020 | 0.2388 |
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- | 0.282 | 86.0 | 1032 | 0.2401 |
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- | 0.282 | 87.0 | 1044 | 0.2302 |
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- | 0.2806 | 88.0 | 1056 | 0.1975 |
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- | 0.2806 | 89.0 | 1068 | 0.2154 |
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- | 0.271 | 90.0 | 1080 | 0.1875 |
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- | 0.271 | 91.0 | 1092 | 0.2032 |
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- | 0.271 | 92.0 | 1104 | 0.2198 |
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- | 0.2695 | 93.0 | 1116 | 0.2018 |
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- | 0.2695 | 94.0 | 1128 | 0.2124 |
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- | 0.2593 | 95.0 | 1140 | 0.2150 |
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- | 0.2593 | 96.0 | 1152 | 0.1841 |
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- | 0.2593 | 97.0 | 1164 | 0.2062 |
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- | 0.2643 | 98.0 | 1176 | 0.1977 |
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- | 0.2643 | 99.0 | 1188 | 0.1847 |
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- | 0.2508 | 100.0 | 1200 | 0.1939 |
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- | 0.2508 | 101.0 | 1212 | 0.2070 |
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- | 0.2508 | 102.0 | 1224 | 0.1943 |
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- | 0.2547 | 103.0 | 1236 | 0.1911 |
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- | 0.2547 | 104.0 | 1248 | 0.1922 |
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- | 0.2512 | 105.0 | 1260 | 0.1988 |
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- | 0.2512 | 106.0 | 1272 | 0.1968 |
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- | 0.2512 | 107.0 | 1284 | 0.1984 |
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- | 0.2465 | 108.0 | 1296 | 0.2030 |
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- | 0.2465 | 109.0 | 1308 | 0.1995 |
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- | 0.2428 | 110.0 | 1320 | 0.1948 |
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- | 0.2428 | 111.0 | 1332 | 0.1969 |
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- | 0.2428 | 112.0 | 1344 | 0.1969 |
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- | 0.2432 | 113.0 | 1356 | 0.1943 |
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- | 0.2432 | 114.0 | 1368 | 0.1949 |
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- | 0.2428 | 115.0 | 1380 | 0.1930 |
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- | 0.2428 | 116.0 | 1392 | 0.1924 |
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- | 0.2428 | 117.0 | 1404 | 0.1948 |
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- | 0.2452 | 118.0 | 1416 | 0.1967 |
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- | 0.2452 | 119.0 | 1428 | 0.1943 |
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- | 0.245 | 120.0 | 1440 | 0.1949 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the None dataset.
18
  It achieves the following results on the evaluation set:
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+ - Loss: 0.1692
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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+ - training_steps: 1440
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:----:|:---------------:|
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+ | No log | 1.0 | 23 | 0.9258 |
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+ | 1.1129 | 2.0 | 46 | 0.8241 |
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+ | 0.8989 | 3.0 | 69 | 0.8080 |
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+ | 0.8799 | 4.0 | 92 | 0.9306 |
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+ | 0.8799 | 5.0 | 115 | 0.5536 |
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+ | 0.6986 | 6.0 | 138 | 0.5199 |
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+ | 0.6088 | 7.0 | 161 | 0.4739 |
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+ | 0.631 | 8.0 | 184 | 0.5007 |
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+ | 0.631 | 9.0 | 207 | 0.6598 |
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+ | 0.5804 | 10.0 | 230 | 0.4345 |
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+ | 0.5656 | 11.0 | 253 | 0.4864 |
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+ | 0.5725 | 12.0 | 276 | 0.3707 |
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+ | 0.5725 | 13.0 | 299 | 0.3357 |
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+ | 0.4953 | 14.0 | 322 | 0.4104 |
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+ | 0.4619 | 15.0 | 345 | 0.3681 |
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+ | 0.4463 | 16.0 | 368 | 0.3045 |
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+ | 0.433 | 17.0 | 391 | 0.3330 |
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+ | 0.433 | 18.0 | 414 | 0.3561 |
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+ | 0.396 | 19.0 | 437 | 0.2583 |
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+ | 0.3845 | 20.0 | 460 | 0.2699 |
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+ | 0.3569 | 21.0 | 483 | 0.2714 |
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+ | 0.3569 | 22.0 | 506 | 0.2978 |
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+ | 0.3574 | 23.0 | 529 | 0.2844 |
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+ | 0.3424 | 24.0 | 552 | 0.2650 |
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+ | 0.35 | 25.0 | 575 | 0.2829 |
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+ | 0.35 | 26.0 | 598 | 0.2533 |
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+ | 0.34 | 27.0 | 621 | 0.2306 |
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+ | 0.3309 | 28.0 | 644 | 0.2348 |
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+ | 0.3297 | 29.0 | 667 | 0.2912 |
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+ | 0.3357 | 30.0 | 690 | 0.2679 |
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+ | 0.3357 | 31.0 | 713 | 0.2685 |
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+ | 0.3267 | 32.0 | 736 | 0.2384 |
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+ | 0.3102 | 33.0 | 759 | 0.2346 |
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+ | 0.3204 | 34.0 | 782 | 0.2850 |
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+ | 0.3204 | 35.0 | 805 | 0.2969 |
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+ | 0.3191 | 36.0 | 828 | 0.2315 |
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+ | 0.3051 | 37.0 | 851 | 0.1958 |
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+ | 0.2825 | 38.0 | 874 | 0.2211 |
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+ | 0.2825 | 39.0 | 897 | 0.2309 |
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+ | 0.2895 | 40.0 | 920 | 0.2610 |
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+ | 0.2891 | 41.0 | 943 | 0.2334 |
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+ | 0.279 | 42.0 | 966 | 0.2149 |
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+ | 0.279 | 43.0 | 989 | 0.2017 |
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+ | 0.2735 | 44.0 | 1012 | 0.2445 |
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+ | 0.2688 | 45.0 | 1035 | 0.2164 |
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+ | 0.2602 | 46.0 | 1058 | 0.1995 |
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+ | 0.2644 | 47.0 | 1081 | 0.1936 |
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+ | 0.2644 | 48.0 | 1104 | 0.1884 |
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+ | 0.2634 | 49.0 | 1127 | 0.1974 |
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+ | 0.2568 | 50.0 | 1150 | 0.1981 |
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+ | 0.2456 | 51.0 | 1173 | 0.1799 |
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+ | 0.2456 | 52.0 | 1196 | 0.1777 |
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+ | 0.2479 | 53.0 | 1219 | 0.1915 |
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+ | 0.2529 | 54.0 | 1242 | 0.1928 |
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+ | 0.2533 | 55.0 | 1265 | 0.1772 |
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+ | 0.2533 | 56.0 | 1288 | 0.1863 |
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+ | 0.2516 | 57.0 | 1311 | 0.1775 |
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+ | 0.2495 | 58.0 | 1334 | 0.1808 |
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+ | 0.2428 | 59.0 | 1357 | 0.1734 |
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+ | 0.2454 | 60.0 | 1380 | 0.1696 |
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+ | 0.2454 | 61.0 | 1403 | 0.1766 |
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+ | 0.2452 | 62.0 | 1426 | 0.1718 |
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+ | 0.2367 | 62.6087 | 1440 | 0.1692 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions