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: 0.1998
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 | 13 | 0.9517 |
| No log | 2.0 | 26 | 0.8438 |
| 1.0443 | 3.0 | 39 | 0.8075 |
| 1.0443 | 4.0 | 52 | 0.8254 |
| 0.861 | 5.0 | 65 | 0.7857 |
| 0.861 | 6.0 | 78 | 0.5834 |
| 0.7566 | 7.0 | 91 | 0.5146 |
| 0.7566 | 8.0 | 104 | 0.6595 |
| 0.7566 | 9.0 | 117 | 0.5407 |
| 0.6339 | 10.0 | 130 | 0.5945 |
| 0.6339 | 11.0 | 143 | 0.4432 |
| 0.5959 | 12.0 | 156 | 0.4546 |
| 0.5959 | 13.0 | 169 | 0.4366 |
| 0.5014 | 14.0 | 182 | 0.5585 |
| 0.5014 | 15.0 | 195 | 0.4149 |
| 0.5014 | 16.0 | 208 | 0.3919 |
| 0.4776 | 17.0 | 221 | 0.3864 |
| 0.4776 | 18.0 | 234 | 0.4003 |
| 0.4489 | 19.0 | 247 | 0.3789 |
| 0.4489 | 20.0 | 260 | 0.3881 |
| 0.4598 | 21.0 | 273 | 0.3729 |
| 0.4598 | 22.0 | 286 | 0.3117 |
| 0.4598 | 23.0 | 299 | 0.3386 |
| 0.4112 | 24.0 | 312 | 0.2830 |
| 0.4112 | 25.0 | 325 | 0.3120 |
| 0.3896 | 26.0 | 338 | 0.4226 |
| 0.3896 | 27.0 | 351 | 0.3717 |
| 0.4167 | 28.0 | 364 | 0.3000 |
| 0.4167 | 29.0 | 377 | 0.3637 |
| 0.4062 | 30.0 | 390 | 0.3542 |
| 0.4062 | 31.0 | 403 | 0.4459 |
| 0.4062 | 32.0 | 416 | 0.3601 |
| 0.4099 | 33.0 | 429 | 0.3175 |
| 0.4099 | 34.0 | 442 | 0.2680 |
| 0.3472 | 35.0 | 455 | 0.2578 |
| 0.3472 | 36.0 | 468 | 0.3001 |
| 0.3591 | 37.0 | 481 | 0.2711 |
| 0.3591 | 38.0 | 494 | 0.2830 |
| 0.3591 | 39.0 | 507 | 0.2656 |
| 0.3412 | 40.0 | 520 | 0.2630 |
| 0.3412 | 41.0 | 533 | 0.3321 |
| 0.3576 | 42.0 | 546 | 0.3430 |
| 0.3576 | 43.0 | 559 | 0.3045 |
| 0.3551 | 44.0 | 572 | 0.2655 |
| 0.3551 | 45.0 | 585 | 0.2492 |
| 0.3551 | 46.0 | 598 | 0.2796 |
| 0.3209 | 47.0 | 611 | 0.2389 |
| 0.3209 | 48.0 | 624 | 0.2839 |
| 0.331 | 49.0 | 637 | 0.3001 |
| 0.331 | 50.0 | 650 | 0.3001 |
| 0.326 | 51.0 | 663 | 0.2871 |
| 0.326 | 52.0 | 676 | 0.2934 |
| 0.326 | 53.0 | 689 | 0.2741 |
| 0.3193 | 54.0 | 702 | 0.2774 |
| 0.3193 | 55.0 | 715 | 0.2753 |
| 0.3078 | 56.0 | 728 | 0.2734 |
| 0.3078 | 57.0 | 741 | 0.3060 |
| 0.2999 | 58.0 | 754 | 0.2680 |
| 0.2999 | 59.0 | 767 | 0.3381 |
| 0.3173 | 60.0 | 780 | 0.3136 |
| 0.3173 | 61.0 | 793 | 0.2993 |
| 0.3173 | 62.0 | 806 | 0.2819 |
| 0.3063 | 63.0 | 819 | 0.3030 |
| 0.3063 | 64.0 | 832 | 0.2549 |
| 0.3143 | 65.0 | 845 | 0.2936 |
| 0.3143 | 66.0 | 858 | 0.2692 |
| 0.3032 | 67.0 | 871 | 0.2773 |
| 0.3032 | 68.0 | 884 | 0.2473 |
| 0.3032 | 69.0 | 897 | 0.2276 |
| 0.2922 | 70.0 | 910 | 0.2365 |
| 0.2922 | 71.0 | 923 | 0.2627 |
| 0.2872 | 72.0 | 936 | 0.2601 |
| 0.2872 | 73.0 | 949 | 0.2449 |
| 0.277 | 74.0 | 962 | 0.2336 |
| 0.277 | 75.0 | 975 | 0.2350 |
| 0.277 | 76.0 | 988 | 0.2542 |
| 0.2739 | 77.0 | 1001 | 0.2455 |
| 0.2739 | 78.0 | 1014 | 0.2323 |
| 0.2695 | 79.0 | 1027 | 0.2636 |
| 0.2695 | 80.0 | 1040 | 0.2430 |
| 0.264 | 81.0 | 1053 | 0.2141 |
| 0.264 | 82.0 | 1066 | 0.2332 |
| 0.264 | 83.0 | 1079 | 0.2138 |
| 0.2557 | 84.0 | 1092 | 0.2153 |
| 0.2557 | 85.0 | 1105 | 0.2193 |
| 0.2456 | 86.0 | 1118 | 0.2001 |
| 0.2456 | 87.0 | 1131 | 0.2222 |
| 0.2466 | 88.0 | 1144 | 0.2170 |
| 0.2466 | 89.0 | 1157 | 0.2059 |
| 0.2451 | 90.0 | 1170 | 0.2115 |
| 0.2451 | 91.0 | 1183 | 0.2139 |
| 0.2451 | 92.0 | 1196 | 0.1982 |
| 0.2409 | 93.0 | 1209 | 0.2185 |
| 0.2409 | 94.0 | 1222 | 0.2201 |
| 0.2468 | 95.0 | 1235 | 0.2157 |
| 0.2468 | 96.0 | 1248 | 0.2095 |
| 0.2408 | 97.0 | 1261 | 0.2045 |
| 0.2408 | 98.0 | 1274 | 0.2149 |
| 0.2408 | 99.0 | 1287 | 0.2038 |
| 0.2377 | 100.0 | 1300 | 0.2150 |
| 0.2377 | 101.0 | 1313 | 0.1925 |
| 0.2334 | 102.0 | 1326 | 0.1960 |
| 0.2334 | 103.0 | 1339 | 0.1942 |
| 0.2346 | 104.0 | 1352 | 0.1971 |
| 0.2346 | 105.0 | 1365 | 0.1953 |
| 0.2346 | 106.0 | 1378 | 0.2019 |
| 0.2375 | 107.0 | 1391 | 0.2035 |
| 0.2375 | 108.0 | 1404 | 0.1993 |
| 0.2273 | 109.0 | 1417 | 0.2046 |
| 0.2273 | 110.0 | 1430 | 0.1983 |
| 0.227 | 111.0 | 1443 | 0.1987 |
| 0.227 | 112.0 | 1456 | 0.1986 |
| 0.227 | 113.0 | 1469 | 0.2039 |
| 0.2272 | 114.0 | 1482 | 0.2023 |
| 0.2272 | 115.0 | 1495 | 0.1990 |
| 0.2255 | 116.0 | 1508 | 0.2005 |
| 0.2255 | 117.0 | 1521 | 0.1992 |
| 0.2323 | 118.0 | 1534 | 0.1980 |
| 0.2323 | 119.0 | 1547 | 0.1995 |
| 0.2273 | 120.0 | 1560 | 0.1998 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.14.4
- Tokenizers 0.19.1