metadata
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: chickens
results: []
chickens
This model is a fine-tuned version of facebook/detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1949
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 120
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 12 | 1.3837 |
| No log | 2.0 | 24 | 0.9192 |
| 1.2199 | 3.0 | 36 | 0.9478 |
| 1.2199 | 4.0 | 48 | 0.8188 |
| 0.9301 | 5.0 | 60 | 0.8648 |
| 0.9301 | 6.0 | 72 | 0.7913 |
| 0.9301 | 7.0 | 84 | 0.8269 |
| 0.834 | 8.0 | 96 | 0.7546 |
| 0.834 | 9.0 | 108 | 0.7128 |
| 0.7676 | 10.0 | 120 | 0.6706 |
| 0.7676 | 11.0 | 132 | 0.6042 |
| 0.7676 | 12.0 | 144 | 0.5586 |
| 0.6807 | 13.0 | 156 | 0.5129 |
| 0.6807 | 14.0 | 168 | 0.4815 |
| 0.5846 | 15.0 | 180 | 0.4724 |
| 0.5846 | 16.0 | 192 | 0.4970 |
| 0.5846 | 17.0 | 204 | 0.4900 |
| 0.5437 | 18.0 | 216 | 0.4985 |
| 0.5437 | 19.0 | 228 | 0.6295 |
| 0.5232 | 20.0 | 240 | 0.5023 |
| 0.5232 | 21.0 | 252 | 0.4312 |
| 0.5232 | 22.0 | 264 | 0.4583 |
| 0.5147 | 23.0 | 276 | 0.4499 |
| 0.5147 | 24.0 | 288 | 0.3438 |
| 0.4613 | 25.0 | 300 | 0.3953 |
| 0.4613 | 26.0 | 312 | 0.3916 |
| 0.4613 | 27.0 | 324 | 0.4285 |
| 0.4288 | 28.0 | 336 | 0.3532 |
| 0.4288 | 29.0 | 348 | 0.3513 |
| 0.4251 | 30.0 | 360 | 0.3761 |
| 0.4251 | 31.0 | 372 | 0.3183 |
| 0.4251 | 32.0 | 384 | 0.3419 |
| 0.3963 | 33.0 | 396 | 0.3186 |
| 0.3963 | 34.0 | 408 | 0.2799 |
| 0.3684 | 35.0 | 420 | 0.3688 |
| 0.3684 | 36.0 | 432 | 0.4035 |
| 0.3684 | 37.0 | 444 | 0.3491 |
| 0.4062 | 38.0 | 456 | 0.3147 |
| 0.4062 | 39.0 | 468 | 0.3333 |
| 0.3745 | 40.0 | 480 | 0.2822 |
| 0.3745 | 41.0 | 492 | 0.2734 |
| 0.3745 | 42.0 | 504 | 0.2816 |
| 0.3461 | 43.0 | 516 | 0.3289 |
| 0.3461 | 44.0 | 528 | 0.3538 |
| 0.3707 | 45.0 | 540 | 0.2969 |
| 0.3707 | 46.0 | 552 | 0.3335 |
| 0.3707 | 47.0 | 564 | 0.3201 |
| 0.3906 | 48.0 | 576 | 0.3262 |
| 0.3906 | 49.0 | 588 | 0.3213 |
| 0.3622 | 50.0 | 600 | 0.2825 |
| 0.3622 | 51.0 | 612 | 0.3111 |
| 0.3622 | 52.0 | 624 | 0.2814 |
| 0.336 | 53.0 | 636 | 0.3242 |
| 0.336 | 54.0 | 648 | 0.2615 |
| 0.3326 | 55.0 | 660 | 0.3107 |
| 0.3326 | 56.0 | 672 | 0.2904 |
| 0.3326 | 57.0 | 684 | 0.2967 |
| 0.3407 | 58.0 | 696 | 0.2818 |
| 0.3407 | 59.0 | 708 | 0.2759 |
| 0.3467 | 60.0 | 720 | 0.2862 |
| 0.3467 | 61.0 | 732 | 0.3529 |
| 0.3467 | 62.0 | 744 | 0.3559 |
| 0.354 | 63.0 | 756 | 0.2403 |
| 0.354 | 64.0 | 768 | 0.2815 |
| 0.3237 | 65.0 | 780 | 0.2819 |
| 0.3237 | 66.0 | 792 | 0.2476 |
| 0.3237 | 67.0 | 804 | 0.3193 |
| 0.3182 | 68.0 | 816 | 0.2444 |
| 0.3182 | 69.0 | 828 | 0.2510 |
| 0.3151 | 70.0 | 840 | 0.2951 |
| 0.3151 | 71.0 | 852 | 0.2389 |
| 0.3151 | 72.0 | 864 | 0.2657 |
| 0.3173 | 73.0 | 876 | 0.2783 |
| 0.3173 | 74.0 | 888 | 0.2791 |
| 0.3283 | 75.0 | 900 | 0.2445 |
| 0.3283 | 76.0 | 912 | 0.2507 |
| 0.3283 | 77.0 | 924 | 0.2778 |
| 0.3041 | 78.0 | 936 | 0.2471 |
| 0.3041 | 79.0 | 948 | 0.2219 |
| 0.2925 | 80.0 | 960 | 0.2767 |
| 0.2925 | 81.0 | 972 | 0.3046 |
| 0.2925 | 82.0 | 984 | 0.2837 |
| 0.3112 | 83.0 | 996 | 0.2710 |
| 0.3112 | 84.0 | 1008 | 0.2399 |
| 0.282 | 85.0 | 1020 | 0.2388 |
| 0.282 | 86.0 | 1032 | 0.2401 |
| 0.282 | 87.0 | 1044 | 0.2302 |
| 0.2806 | 88.0 | 1056 | 0.1975 |
| 0.2806 | 89.0 | 1068 | 0.2154 |
| 0.271 | 90.0 | 1080 | 0.1875 |
| 0.271 | 91.0 | 1092 | 0.2032 |
| 0.271 | 92.0 | 1104 | 0.2198 |
| 0.2695 | 93.0 | 1116 | 0.2018 |
| 0.2695 | 94.0 | 1128 | 0.2124 |
| 0.2593 | 95.0 | 1140 | 0.2150 |
| 0.2593 | 96.0 | 1152 | 0.1841 |
| 0.2593 | 97.0 | 1164 | 0.2062 |
| 0.2643 | 98.0 | 1176 | 0.1977 |
| 0.2643 | 99.0 | 1188 | 0.1847 |
| 0.2508 | 100.0 | 1200 | 0.1939 |
| 0.2508 | 101.0 | 1212 | 0.2070 |
| 0.2508 | 102.0 | 1224 | 0.1943 |
| 0.2547 | 103.0 | 1236 | 0.1911 |
| 0.2547 | 104.0 | 1248 | 0.1922 |
| 0.2512 | 105.0 | 1260 | 0.1988 |
| 0.2512 | 106.0 | 1272 | 0.1968 |
| 0.2512 | 107.0 | 1284 | 0.1984 |
| 0.2465 | 108.0 | 1296 | 0.2030 |
| 0.2465 | 109.0 | 1308 | 0.1995 |
| 0.2428 | 110.0 | 1320 | 0.1948 |
| 0.2428 | 111.0 | 1332 | 0.1969 |
| 0.2428 | 112.0 | 1344 | 0.1969 |
| 0.2432 | 113.0 | 1356 | 0.1943 |
| 0.2432 | 114.0 | 1368 | 0.1949 |
| 0.2428 | 115.0 | 1380 | 0.1930 |
| 0.2428 | 116.0 | 1392 | 0.1924 |
| 0.2428 | 117.0 | 1404 | 0.1948 |
| 0.2452 | 118.0 | 1416 | 0.1967 |
| 0.2452 | 119.0 | 1428 | 0.1943 |
| 0.245 | 120.0 | 1440 | 0.1949 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.14.4
- Tokenizers 0.19.1