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: 0.1943
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 | 0.9906 |
| No log | 2.0 | 26 | 0.8173 |
| 1.1275 | 3.0 | 39 | 0.7421 |
| 1.1275 | 4.0 | 52 | 0.6724 |
| 0.7856 | 5.0 | 65 | 0.6512 |
| 0.7856 | 6.0 | 78 | 0.6049 |
| 0.7138 | 7.0 | 91 | 0.5991 |
| 0.7138 | 8.0 | 104 | 0.4816 |
| 0.7138 | 9.0 | 117 | 0.4908 |
| 0.5948 | 10.0 | 130 | 0.5110 |
| 0.5948 | 11.0 | 143 | 0.6477 |
| 0.6058 | 12.0 | 156 | 0.5520 |
| 0.6058 | 13.0 | 169 | 0.5291 |
| 0.5792 | 14.0 | 182 | 0.4270 |
| 0.5792 | 15.0 | 195 | 0.4583 |
| 0.5792 | 16.0 | 208 | 0.3994 |
| 0.5239 | 17.0 | 221 | 0.4074 |
| 0.5239 | 18.0 | 234 | 0.3419 |
| 0.4717 | 19.0 | 247 | 0.3592 |
| 0.4717 | 20.0 | 260 | 0.2978 |
| 0.4381 | 21.0 | 273 | 0.3756 |
| 0.4381 | 22.0 | 286 | 0.3461 |
| 0.4381 | 23.0 | 299 | 0.3594 |
| 0.4445 | 24.0 | 312 | 0.3783 |
| 0.4445 | 25.0 | 325 | 0.3260 |
| 0.4077 | 26.0 | 338 | 0.2947 |
| 0.4077 | 27.0 | 351 | 0.3058 |
| 0.3928 | 28.0 | 364 | 0.3364 |
| 0.3928 | 29.0 | 377 | 0.2904 |
| 0.3749 | 30.0 | 390 | 0.3442 |
| 0.3749 | 31.0 | 403 | 0.3432 |
| 0.3749 | 32.0 | 416 | 0.2989 |
| 0.41 | 33.0 | 429 | 0.2860 |
| 0.41 | 34.0 | 442 | 0.2915 |
| 0.3624 | 35.0 | 455 | 0.2928 |
| 0.3624 | 36.0 | 468 | 0.2364 |
| 0.3405 | 37.0 | 481 | 0.2878 |
| 0.3405 | 38.0 | 494 | 0.2816 |
| 0.3405 | 39.0 | 507 | 0.3071 |
| 0.3444 | 40.0 | 520 | 0.2928 |
| 0.3444 | 41.0 | 533 | 0.2528 |
| 0.3323 | 42.0 | 546 | 0.3098 |
| 0.3323 | 43.0 | 559 | 0.2817 |
| 0.3094 | 44.0 | 572 | 0.2796 |
| 0.3094 | 45.0 | 585 | 0.2652 |
| 0.3094 | 46.0 | 598 | 0.3038 |
| 0.3265 | 47.0 | 611 | 0.2523 |
| 0.3265 | 48.0 | 624 | 0.2773 |
| 0.3109 | 49.0 | 637 | 0.2644 |
| 0.3109 | 50.0 | 650 | 0.2626 |
| 0.3116 | 51.0 | 663 | 0.2510 |
| 0.3116 | 52.0 | 676 | 0.2814 |
| 0.3116 | 53.0 | 689 | 0.2355 |
| 0.2924 | 54.0 | 702 | 0.2618 |
| 0.2924 | 55.0 | 715 | 0.2638 |
| 0.3006 | 56.0 | 728 | 0.3032 |
| 0.3006 | 57.0 | 741 | 0.2936 |
| 0.3044 | 58.0 | 754 | 0.2722 |
| 0.3044 | 59.0 | 767 | 0.2377 |
| 0.279 | 60.0 | 780 | 0.2741 |
| 0.279 | 61.0 | 793 | 0.2514 |
| 0.279 | 62.0 | 806 | 0.2392 |
| 0.292 | 63.0 | 819 | 0.2281 |
| 0.292 | 64.0 | 832 | 0.2189 |
| 0.2773 | 65.0 | 845 | 0.2053 |
| 0.2773 | 66.0 | 858 | 0.2256 |
| 0.2778 | 67.0 | 871 | 0.2748 |
| 0.2778 | 68.0 | 884 | 0.2286 |
| 0.2778 | 69.0 | 897 | 0.2033 |
| 0.2641 | 70.0 | 910 | 0.2242 |
| 0.2641 | 71.0 | 923 | 0.2285 |
| 0.2667 | 72.0 | 936 | 0.2103 |
| 0.2667 | 73.0 | 949 | 0.2307 |
| 0.2542 | 74.0 | 962 | 0.2209 |
| 0.2542 | 75.0 | 975 | 0.2390 |
| 0.2542 | 76.0 | 988 | 0.2503 |
| 0.2621 | 77.0 | 1001 | 0.2405 |
| 0.2621 | 78.0 | 1014 | 0.2239 |
| 0.2493 | 79.0 | 1027 | 0.2441 |
| 0.2493 | 80.0 | 1040 | 0.2465 |
| 0.2516 | 81.0 | 1053 | 0.2167 |
| 0.2516 | 82.0 | 1066 | 0.2306 |
| 0.2516 | 83.0 | 1079 | 0.2263 |
| 0.2409 | 84.0 | 1092 | 0.2090 |
| 0.2409 | 85.0 | 1105 | 0.2158 |
| 0.234 | 86.0 | 1118 | 0.2212 |
| 0.234 | 87.0 | 1131 | 0.2237 |
| 0.2429 | 88.0 | 1144 | 0.2236 |
| 0.2429 | 89.0 | 1157 | 0.2095 |
| 0.2391 | 90.0 | 1170 | 0.2047 |
| 0.2391 | 91.0 | 1183 | 0.1991 |
| 0.2391 | 92.0 | 1196 | 0.2139 |
| 0.227 | 93.0 | 1209 | 0.2038 |
| 0.227 | 94.0 | 1222 | 0.2042 |
| 0.2237 | 95.0 | 1235 | 0.2019 |
| 0.2237 | 96.0 | 1248 | 0.2047 |
| 0.2263 | 97.0 | 1261 | 0.1969 |
| 0.2263 | 98.0 | 1274 | 0.2148 |
| 0.2263 | 99.0 | 1287 | 0.1865 |
| 0.2229 | 100.0 | 1300 | 0.2142 |
| 0.2229 | 101.0 | 1313 | 0.1932 |
| 0.2157 | 102.0 | 1326 | 0.1916 |
| 0.2157 | 103.0 | 1339 | 0.2002 |
| 0.2236 | 104.0 | 1352 | 0.1924 |
| 0.2236 | 105.0 | 1365 | 0.1953 |
| 0.2236 | 106.0 | 1378 | 0.1995 |
| 0.2216 | 107.0 | 1391 | 0.1997 |
| 0.2216 | 108.0 | 1404 | 0.1960 |
| 0.2201 | 109.0 | 1417 | 0.1969 |
| 0.2201 | 110.0 | 1430 | 0.1980 |
| 0.2183 | 111.0 | 1443 | 0.2006 |
| 0.2183 | 112.0 | 1456 | 0.1976 |
| 0.2183 | 113.0 | 1469 | 0.1956 |
| 0.2175 | 114.0 | 1482 | 0.1969 |
| 0.2175 | 115.0 | 1495 | 0.1967 |
| 0.2198 | 116.0 | 1508 | 0.1956 |
| 0.2198 | 117.0 | 1521 | 0.1938 |
| 0.2133 | 118.0 | 1534 | 0.1944 |
| 0.2133 | 119.0 | 1547 | 0.1942 |
| 0.2168 | 120.0 | 1560 | 0.1943 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.14.4
- Tokenizers 0.19.1