File size: 12,576 Bytes
37394bd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 |
---
license: apache-2.0
base_model: PekingU/rtdetr_r50vd
tags:
- generated_from_trainer
model-index:
- name: PekingU_rtdetr_r50vd_cppe5_jw_1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# PekingU_rtdetr_r50vd_cppe5_jw_1
This model is a fine-tuned version of [PekingU/rtdetr_r50vd](https://huggingface.co/PekingU/rtdetr_r50vd) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 12.2150
- Map: 0.3305
- Map 50: 0.6332
- Map 75: 0.2924
- Map Small: 0.1087
- Map Medium: 0.2627
- Map Large: 0.5123
- Mar 1: 0.3018
- Mar 10: 0.4833
- Mar 100: 0.5384
- Mar Small: 0.3203
- Mar Medium: 0.478
- Mar Large: 0.7067
- Map Coverall: 0.5473
- Mar 100 Coverall: 0.7158
- Map Face Shield: 0.3566
- Mar 100 Face Shield: 0.6063
- Map Gloves: 0.2415
- Mar 100 Gloves: 0.4621
- Map Goggles: 0.2167
- Mar 100 Goggles: 0.4431
- Map Mask: 0.2905
- Mar 100 Mask: 0.4649
## 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
| No log | 1.0 | 107 | 13.6921 | 0.2046 | 0.3735 | 0.1947 | 0.068 | 0.1841 | 0.3025 | 0.2454 | 0.4315 | 0.4921 | 0.3014 | 0.4276 | 0.6762 | 0.4274 | 0.6712 | 0.0666 | 0.4848 | 0.116 | 0.3835 | 0.0986 | 0.4277 | 0.3143 | 0.4933 |
| No log | 2.0 | 214 | 12.2598 | 0.2507 | 0.4883 | 0.2181 | 0.1039 | 0.2171 | 0.3973 | 0.2841 | 0.4745 | 0.537 | 0.3358 | 0.4862 | 0.6937 | 0.4926 | 0.6901 | 0.1416 | 0.5722 | 0.1704 | 0.4478 | 0.1357 | 0.4769 | 0.3134 | 0.4982 |
| No log | 3.0 | 321 | 11.9174 | 0.2813 | 0.5306 | 0.2637 | 0.0892 | 0.2413 | 0.4566 | 0.2967 | 0.5005 | 0.5551 | 0.3245 | 0.5093 | 0.7123 | 0.5103 | 0.7081 | 0.214 | 0.6076 | 0.1968 | 0.4679 | 0.1747 | 0.4769 | 0.3108 | 0.5151 |
| No log | 4.0 | 428 | 11.9953 | 0.3027 | 0.5694 | 0.2825 | 0.1123 | 0.2568 | 0.4667 | 0.3125 | 0.5034 | 0.5641 | 0.3481 | 0.5136 | 0.7092 | 0.5386 | 0.7086 | 0.2789 | 0.6316 | 0.2018 | 0.4563 | 0.2069 | 0.5123 | 0.2872 | 0.5116 |
| 20.3574 | 5.0 | 535 | 11.9065 | 0.3094 | 0.6001 | 0.2701 | 0.111 | 0.2743 | 0.4646 | 0.3037 | 0.4914 | 0.5537 | 0.3398 | 0.5075 | 0.7127 | 0.5381 | 0.6973 | 0.2998 | 0.6101 | 0.1896 | 0.4629 | 0.2168 | 0.5077 | 0.3028 | 0.4907 |
| 20.3574 | 6.0 | 642 | 11.7344 | 0.3247 | 0.6261 | 0.2856 | 0.1295 | 0.2678 | 0.511 | 0.3124 | 0.4959 | 0.5571 | 0.3649 | 0.4939 | 0.7194 | 0.5191 | 0.6851 | 0.3164 | 0.6013 | 0.2084 | 0.4808 | 0.2565 | 0.5138 | 0.3234 | 0.5044 |
| 20.3574 | 7.0 | 749 | 11.8164 | 0.3334 | 0.6308 | 0.3036 | 0.1224 | 0.2636 | 0.5347 | 0.3184 | 0.5033 | 0.5614 | 0.3559 | 0.5025 | 0.7285 | 0.5403 | 0.6932 | 0.3151 | 0.6278 | 0.213 | 0.471 | 0.2695 | 0.5062 | 0.3293 | 0.5089 |
| 20.3574 | 8.0 | 856 | 11.7534 | 0.3368 | 0.6435 | 0.3015 | 0.1196 | 0.273 | 0.5312 | 0.3174 | 0.4979 | 0.5609 | 0.3269 | 0.501 | 0.7413 | 0.558 | 0.7104 | 0.3457 | 0.6316 | 0.2289 | 0.4754 | 0.2288 | 0.4908 | 0.3223 | 0.4964 |
| 20.3574 | 9.0 | 963 | 11.8592 | 0.3326 | 0.6485 | 0.2827 | 0.1199 | 0.2747 | 0.5222 | 0.3153 | 0.501 | 0.5546 | 0.3213 | 0.4936 | 0.729 | 0.5518 | 0.6986 | 0.3311 | 0.6 | 0.2148 | 0.4839 | 0.236 | 0.4785 | 0.3295 | 0.512 |
| 12.6823 | 10.0 | 1070 | 11.9904 | 0.333 | 0.6405 | 0.2978 | 0.1135 | 0.2741 | 0.5196 | 0.3091 | 0.4947 | 0.5467 | 0.3229 | 0.4953 | 0.7097 | 0.5403 | 0.7018 | 0.3419 | 0.6215 | 0.2384 | 0.4688 | 0.2325 | 0.4615 | 0.3117 | 0.48 |
| 12.6823 | 11.0 | 1177 | 11.9472 | 0.334 | 0.6479 | 0.2904 | 0.1056 | 0.2845 | 0.5164 | 0.314 | 0.505 | 0.5605 | 0.3419 | 0.4978 | 0.7316 | 0.5548 | 0.7023 | 0.3488 | 0.6089 | 0.229 | 0.5027 | 0.2365 | 0.5 | 0.301 | 0.4889 |
| 12.6823 | 12.0 | 1284 | 12.0204 | 0.336 | 0.6377 | 0.3032 | 0.1228 | 0.2728 | 0.5224 | 0.3162 | 0.5077 | 0.5591 | 0.3479 | 0.5015 | 0.7214 | 0.5353 | 0.6896 | 0.3297 | 0.6025 | 0.2531 | 0.5031 | 0.252 | 0.5031 | 0.3099 | 0.4969 |
| 12.6823 | 13.0 | 1391 | 11.9460 | 0.3373 | 0.6461 | 0.2912 | 0.1245 | 0.2783 | 0.5243 | 0.3113 | 0.502 | 0.5521 | 0.3388 | 0.4936 | 0.7192 | 0.5445 | 0.6986 | 0.3387 | 0.6013 | 0.2517 | 0.4893 | 0.2403 | 0.4846 | 0.3114 | 0.4867 |
| 12.6823 | 14.0 | 1498 | 11.9051 | 0.3523 | 0.6617 | 0.3226 | 0.136 | 0.2944 | 0.5363 | 0.3223 | 0.5036 | 0.5558 | 0.3249 | 0.508 | 0.7127 | 0.57 | 0.709 | 0.3597 | 0.6076 | 0.2491 | 0.5049 | 0.2586 | 0.4662 | 0.3239 | 0.4916 |
| 11.1387 | 15.0 | 1605 | 12.0044 | 0.3399 | 0.6562 | 0.2971 | 0.1349 | 0.2898 | 0.5089 | 0.3074 | 0.5 | 0.556 | 0.3511 | 0.4995 | 0.7189 | 0.5576 | 0.7144 | 0.338 | 0.581 | 0.2422 | 0.4946 | 0.2619 | 0.4985 | 0.3 | 0.4916 |
| 11.1387 | 16.0 | 1712 | 12.2005 | 0.3263 | 0.6241 | 0.2928 | 0.1109 | 0.2512 | 0.5052 | 0.3029 | 0.4896 | 0.5467 | 0.3166 | 0.4913 | 0.704 | 0.5254 | 0.7005 | 0.3614 | 0.6101 | 0.2504 | 0.5049 | 0.2274 | 0.4477 | 0.267 | 0.4702 |
| 11.1387 | 17.0 | 1819 | 12.0237 | 0.3394 | 0.6504 | 0.3072 | 0.1154 | 0.2833 | 0.5157 | 0.3127 | 0.4958 | 0.5516 | 0.3447 | 0.5022 | 0.7017 | 0.5558 | 0.7009 | 0.353 | 0.6089 | 0.2552 | 0.4924 | 0.2226 | 0.4708 | 0.3103 | 0.4849 |
| 11.1387 | 18.0 | 1926 | 12.1186 | 0.3327 | 0.6432 | 0.2865 | 0.1113 | 0.2699 | 0.5206 | 0.3047 | 0.4767 | 0.5402 | 0.3143 | 0.4822 | 0.7094 | 0.5491 | 0.7063 | 0.3614 | 0.6076 | 0.2396 | 0.4799 | 0.2131 | 0.4462 | 0.3002 | 0.4609 |
| 10.0798 | 19.0 | 2033 | 12.0813 | 0.3357 | 0.6531 | 0.2953 | 0.1239 | 0.2789 | 0.5139 | 0.3065 | 0.4932 | 0.5437 | 0.337 | 0.4774 | 0.7108 | 0.5488 | 0.7068 | 0.3669 | 0.6127 | 0.2413 | 0.4661 | 0.23 | 0.4615 | 0.2914 | 0.4716 |
| 10.0798 | 20.0 | 2140 | 12.1951 | 0.3343 | 0.6419 | 0.3053 | 0.1129 | 0.2649 | 0.5183 | 0.3102 | 0.4806 | 0.5394 | 0.3237 | 0.4768 | 0.7028 | 0.5574 | 0.7104 | 0.3622 | 0.6013 | 0.2465 | 0.4768 | 0.2126 | 0.4338 | 0.2927 | 0.4747 |
| 10.0798 | 21.0 | 2247 | 12.2319 | 0.3353 | 0.6449 | 0.2919 | 0.111 | 0.2746 | 0.5182 | 0.3082 | 0.4866 | 0.5404 | 0.3251 | 0.4866 | 0.7057 | 0.5494 | 0.7117 | 0.3628 | 0.6051 | 0.2454 | 0.4777 | 0.2196 | 0.4308 | 0.2992 | 0.4769 |
| 10.0798 | 22.0 | 2354 | 12.2877 | 0.3294 | 0.6321 | 0.2919 | 0.1089 | 0.261 | 0.5186 | 0.3053 | 0.4851 | 0.5447 | 0.3214 | 0.4871 | 0.7145 | 0.5372 | 0.7077 | 0.3567 | 0.6316 | 0.2353 | 0.4723 | 0.2212 | 0.44 | 0.2967 | 0.472 |
| 10.0798 | 23.0 | 2461 | 12.1634 | 0.3319 | 0.6397 | 0.3058 | 0.1157 | 0.2597 | 0.5252 | 0.3122 | 0.4853 | 0.5394 | 0.3303 | 0.483 | 0.707 | 0.5459 | 0.7117 | 0.3409 | 0.5886 | 0.2364 | 0.4737 | 0.2308 | 0.4492 | 0.3055 | 0.4738 |
| 9.3418 | 24.0 | 2568 | 12.1011 | 0.3331 | 0.6406 | 0.2928 | 0.1156 | 0.2575 | 0.5196 | 0.3056 | 0.4807 | 0.539 | 0.3326 | 0.4804 | 0.7006 | 0.556 | 0.7176 | 0.3524 | 0.6038 | 0.2341 | 0.4603 | 0.2233 | 0.4477 | 0.2999 | 0.4658 |
| 9.3418 | 25.0 | 2675 | 12.3668 | 0.3304 | 0.6382 | 0.2966 | 0.1091 | 0.2597 | 0.5184 | 0.305 | 0.4758 | 0.5322 | 0.3251 | 0.4719 | 0.6994 | 0.5502 | 0.7104 | 0.3498 | 0.5949 | 0.2376 | 0.4643 | 0.2223 | 0.4262 | 0.2921 | 0.4653 |
| 9.3418 | 26.0 | 2782 | 12.1546 | 0.3373 | 0.6453 | 0.2976 | 0.1169 | 0.2658 | 0.5251 | 0.3092 | 0.4862 | 0.5425 | 0.3409 | 0.4803 | 0.7113 | 0.5548 | 0.7095 | 0.3569 | 0.6152 | 0.2476 | 0.4612 | 0.2262 | 0.4646 | 0.3009 | 0.4622 |
| 9.3418 | 27.0 | 2889 | 12.2520 | 0.3326 | 0.6367 | 0.2929 | 0.1101 | 0.2617 | 0.5187 | 0.304 | 0.4815 | 0.5366 | 0.3183 | 0.4799 | 0.7078 | 0.5496 | 0.709 | 0.3546 | 0.6076 | 0.2416 | 0.4594 | 0.2189 | 0.4492 | 0.2983 | 0.4578 |
| 9.3418 | 28.0 | 2996 | 12.2222 | 0.3312 | 0.6378 | 0.2931 | 0.1093 | 0.2587 | 0.5152 | 0.3034 | 0.4821 | 0.5379 | 0.3194 | 0.4758 | 0.7086 | 0.5549 | 0.7108 | 0.3513 | 0.6025 | 0.2382 | 0.4612 | 0.2156 | 0.4523 | 0.2962 | 0.4627 |
| 8.908 | 29.0 | 3103 | 12.2006 | 0.3346 | 0.6397 | 0.2931 | 0.1112 | 0.2634 | 0.5211 | 0.3047 | 0.4837 | 0.5396 | 0.329 | 0.4763 | 0.71 | 0.5522 | 0.7144 | 0.3559 | 0.6 | 0.2435 | 0.4647 | 0.2193 | 0.4523 | 0.302 | 0.4667 |
| 8.908 | 30.0 | 3210 | 12.2150 | 0.3305 | 0.6332 | 0.2924 | 0.1087 | 0.2627 | 0.5123 | 0.3018 | 0.4833 | 0.5384 | 0.3203 | 0.478 | 0.7067 | 0.5473 | 0.7158 | 0.3566 | 0.6063 | 0.2415 | 0.4621 | 0.2167 | 0.4431 | 0.2905 | 0.4649 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.5.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
|