File size: 10,952 Bytes
cdb210c |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 |
---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_v2_r101vd
tags:
- generated_from_trainer
model-index:
- name: rtdetr-v2-r101-cppe5-finetune-2
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. -->
# rtdetr-v2-r101-cppe5-finetune-2
This model is a fine-tuned version of [PekingU/rtdetr_v2_r101vd](https://huggingface.co/PekingU/rtdetr_v2_r101vd) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 9.5258
- Map: 0.3781
- Map 50: 0.9125
- Map 75: 0.2023
- Map Small: 0.2722
- Map Medium: 0.4358
- Map Large: 0.4439
- Mar 1: 0.4279
- Mar 10: 0.6136
- Mar 100: 0.6664
- Mar Small: 0.6158
- Mar Medium: 0.701
- Mar Large: 0.6333
## 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: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 50
### 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|
| No log | 1.0 | 313 | 18.7992 | 0.0102 | 0.037 | 0.0016 | 0.0193 | 0.023 | 0.0 | 0.0444 | 0.1863 | 0.2535 | 0.253 | 0.2555 | 0.0 |
| 112.163 | 2.0 | 626 | 14.0671 | 0.0806 | 0.265 | 0.0204 | 0.0711 | 0.0931 | 0.1998 | 0.1649 | 0.3478 | 0.4882 | 0.4476 | 0.5154 | 0.5667 |
| 112.163 | 3.0 | 939 | 13.0106 | 0.1549 | 0.5077 | 0.0356 | 0.1316 | 0.1788 | 0.2388 | 0.2393 | 0.4002 | 0.4952 | 0.4637 | 0.5172 | 0.4 |
| 12.4154 | 4.0 | 1252 | 12.8674 | 0.1861 | 0.578 | 0.0506 | 0.1487 | 0.2151 | 0.3809 | 0.2786 | 0.4329 | 0.5228 | 0.5074 | 0.5334 | 0.5 |
| 10.9002 | 5.0 | 1565 | 12.7759 | 0.1994 | 0.6122 | 0.0592 | 0.1562 | 0.2337 | 0.4435 | 0.2923 | 0.4511 | 0.5369 | 0.5092 | 0.5555 | 0.5667 |
| 10.9002 | 6.0 | 1878 | 12.9410 | 0.2477 | 0.6845 | 0.1046 | 0.1891 | 0.2878 | 0.4869 | 0.3295 | 0.4896 | 0.5643 | 0.5301 | 0.5872 | 0.6333 |
| 10.0597 | 7.0 | 2191 | 12.0453 | 0.2511 | 0.7021 | 0.092 | 0.1894 | 0.2916 | 0.4639 | 0.3144 | 0.4984 | 0.5683 | 0.5179 | 0.6024 | 0.6 |
| 9.4738 | 8.0 | 2504 | 11.6443 | 0.262 | 0.6911 | 0.1112 | 0.2077 | 0.3015 | 0.2426 | 0.3408 | 0.5317 | 0.5898 | 0.5452 | 0.6209 | 0.4667 |
| 9.4738 | 9.0 | 2817 | 11.4795 | 0.3091 | 0.7994 | 0.1487 | 0.2497 | 0.3488 | 0.3159 | 0.3764 | 0.5331 | 0.611 | 0.5664 | 0.6427 | 0.4 |
| 9.0887 | 10.0 | 3130 | 11.0460 | 0.3147 | 0.8058 | 0.1438 | 0.2394 | 0.365 | 0.469 | 0.3837 | 0.5331 | 0.5933 | 0.5301 | 0.6366 | 0.5333 |
| 9.0887 | 11.0 | 3443 | 10.8509 | 0.3038 | 0.7871 | 0.1337 | 0.214 | 0.3601 | 0.3414 | 0.3804 | 0.5429 | 0.5945 | 0.5435 | 0.6304 | 0.4 |
| 8.7187 | 12.0 | 3756 | 11.2568 | 0.2689 | 0.7366 | 0.1041 | 0.1987 | 0.3154 | 0.3722 | 0.3456 | 0.5245 | 0.5972 | 0.5402 | 0.6362 | 0.5667 |
| 8.5299 | 13.0 | 4069 | 10.6576 | 0.2818 | 0.7436 | 0.1189 | 0.2007 | 0.3285 | 0.2467 | 0.3433 | 0.5424 | 0.6164 | 0.5732 | 0.6466 | 0.5 |
| 8.5299 | 14.0 | 4382 | 10.3815 | 0.2688 | 0.6636 | 0.1296 | 0.1923 | 0.3198 | 0.395 | 0.3618 | 0.5586 | 0.6085 | 0.5518 | 0.6482 | 0.4333 |
| 8.2714 | 15.0 | 4695 | 10.2251 | 0.2846 | 0.7427 | 0.1324 | 0.1992 | 0.3356 | 0.3412 | 0.3408 | 0.5538 | 0.6187 | 0.5554 | 0.6623 | 0.5333 |
| 8.0708 | 16.0 | 5008 | 10.4468 | 0.2912 | 0.7585 | 0.1371 | 0.188 | 0.3503 | 0.2716 | 0.3442 | 0.5606 | 0.6252 | 0.5839 | 0.6551 | 0.3333 |
| 8.0708 | 17.0 | 5321 | 10.0924 | 0.3174 | 0.8149 | 0.1384 | 0.2167 | 0.3764 | 0.4464 | 0.3772 | 0.5462 | 0.6038 | 0.5426 | 0.6462 | 0.5 |
| 7.8789 | 18.0 | 5634 | 10.1511 | 0.292 | 0.7808 | 0.1069 | 0.1984 | 0.3441 | 0.4159 | 0.3466 | 0.5514 | 0.6103 | 0.5554 | 0.6484 | 0.5 |
| 7.8789 | 19.0 | 5947 | 10.0809 | 0.2872 | 0.7423 | 0.1304 | 0.1846 | 0.3477 | 0.3738 | 0.3546 | 0.558 | 0.6196 | 0.556 | 0.6638 | 0.4667 |
| 7.7461 | 20.0 | 6260 | 9.7884 | 0.3327 | 0.8237 | 0.1515 | 0.2486 | 0.3814 | 0.4109 | 0.396 | 0.579 | 0.6268 | 0.586 | 0.6555 | 0.4667 |
| 7.6557 | 21.0 | 6573 | 9.9407 | 0.3006 | 0.7914 | 0.1273 | 0.1849 | 0.3632 | 0.442 | 0.3455 | 0.5555 | 0.6118 | 0.5673 | 0.6429 | 0.4667 |
| 7.6557 | 22.0 | 6886 | 9.7508 | 0.3278 | 0.8365 | 0.1451 | 0.2254 | 0.3855 | 0.4052 | 0.372 | 0.5611 | 0.6179 | 0.567 | 0.6524 | 0.6333 |
| 7.4889 | 23.0 | 7199 | 9.9115 | 0.3163 | 0.8201 | 0.1201 | 0.2166 | 0.3695 | 0.4521 | 0.3826 | 0.566 | 0.6277 | 0.5869 | 0.6561 | 0.5333 |
| 7.4078 | 24.0 | 7512 | 9.9078 | 0.3068 | 0.7968 | 0.1297 | 0.1912 | 0.3724 | 0.5057 | 0.3533 | 0.5677 | 0.6291 | 0.5634 | 0.6743 | 0.5333 |
| 7.4078 | 25.0 | 7825 | 9.9138 | 0.2985 | 0.7844 | 0.1291 | 0.1905 | 0.3604 | 0.499 | 0.3514 | 0.5645 | 0.6385 | 0.5744 | 0.683 | 0.5 |
| 7.3325 | 26.0 | 8138 | 9.6711 | 0.3194 | 0.8042 | 0.1664 | 0.2146 | 0.3795 | 0.3995 | 0.3785 | 0.5969 | 0.6546 | 0.5905 | 0.6992 | 0.5 |
| 7.3325 | 27.0 | 8451 | 10.1850 | 0.2888 | 0.7886 | 0.1142 | 0.1822 | 0.3504 | 0.4257 | 0.3229 | 0.5677 | 0.6307 | 0.5616 | 0.6781 | 0.5667 |
| 7.2804 | 28.0 | 8764 | 10.1133 | 0.3185 | 0.8264 | 0.1482 | 0.2248 | 0.3728 | 0.4663 | 0.3688 | 0.5832 | 0.6509 | 0.5872 | 0.6953 | 0.4667 |
| 7.2029 | 29.0 | 9077 | 9.5707 | 0.3228 | 0.8097 | 0.1547 | 0.2271 | 0.3774 | 0.4653 | 0.3957 | 0.6044 | 0.6565 | 0.6071 | 0.6913 | 0.4667 |
| 7.2029 | 30.0 | 9390 | 10.1563 | 0.3377 | 0.8745 | 0.1421 | 0.2499 | 0.3885 | 0.3663 | 0.3789 | 0.5962 | 0.648 | 0.5988 | 0.683 | 0.4 |
| 7.0825 | 31.0 | 9703 | 9.8796 | 0.3364 | 0.8697 | 0.1503 | 0.242 | 0.3886 | 0.4629 | 0.3754 | 0.606 | 0.6556 | 0.6006 | 0.6939 | 0.5 |
| 7.026 | 32.0 | 10016 | 9.8638 | 0.345 | 0.8834 | 0.1628 | 0.2468 | 0.4006 | 0.4779 | 0.3856 | 0.6067 | 0.6615 | 0.6149 | 0.6937 | 0.5667 |
| 7.026 | 33.0 | 10329 | 9.6067 | 0.3561 | 0.8764 | 0.1902 | 0.2453 | 0.4162 | 0.399 | 0.3958 | 0.608 | 0.6585 | 0.6074 | 0.6947 | 0.4 |
| 6.8795 | 34.0 | 10642 | 9.5258 | 0.3781 | 0.9125 | 0.2023 | 0.2722 | 0.4358 | 0.4439 | 0.4279 | 0.6136 | 0.6664 | 0.6158 | 0.701 | 0.6333 |
| 6.8795 | 35.0 | 10955 | 9.4449 | 0.368 | 0.9007 | 0.188 | 0.2706 | 0.4204 | 0.5 | 0.4066 | 0.6088 | 0.6685 | 0.6253 | 0.699 | 0.5 |
| 6.7461 | 36.0 | 11268 | 9.2644 | 0.3658 | 0.8989 | 0.1945 | 0.2671 | 0.419 | 0.4653 | 0.4136 | 0.6142 | 0.6635 | 0.6202 | 0.6941 | 0.4667 |
| 6.64 | 37.0 | 11581 | 9.2426 | 0.3645 | 0.9017 | 0.1894 | 0.2627 | 0.4184 | 0.3975 | 0.4108 | 0.6078 | 0.6507 | 0.5997 | 0.6866 | 0.4333 |
| 6.64 | 38.0 | 11894 | 9.3995 | 0.3721 | 0.899 | 0.1976 | 0.2764 | 0.4243 | 0.4664 | 0.4192 | 0.6066 | 0.6544 | 0.6068 | 0.6877 | 0.5 |
| 6.4988 | 39.0 | 12207 | 9.4093 | 0.3769 | 0.9078 | 0.1964 | 0.2918 | 0.4253 | 0.4664 | 0.4288 | 0.6064 | 0.6531 | 0.6021 | 0.6887 | 0.5 |
| 6.4018 | 40.0 | 12520 | 9.3955 | 0.3615 | 0.8954 | 0.1759 | 0.2773 | 0.4089 | 0.4663 | 0.4116 | 0.6028 | 0.6546 | 0.5982 | 0.6941 | 0.4667 |
| 6.4018 | 41.0 | 12833 | 9.3966 | 0.3711 | 0.8973 | 0.1989 | 0.2758 | 0.4238 | 0.4993 | 0.421 | 0.6102 | 0.6635 | 0.6152 | 0.6968 | 0.6 |
| 6.3285 | 42.0 | 13146 | 9.4656 | 0.3655 | 0.8967 | 0.1968 | 0.2785 | 0.4172 | 0.4694 | 0.4245 | 0.6163 | 0.6701 | 0.6131 | 0.7097 | 0.5333 |
| 6.3285 | 43.0 | 13459 | 9.4390 | 0.3728 | 0.9149 | 0.1933 | 0.2914 | 0.419 | 0.4663 | 0.4295 | 0.6202 | 0.6675 | 0.6187 | 0.7018 | 0.4667 |
| 6.2397 | 44.0 | 13772 | 9.3682 | 0.3636 | 0.8795 | 0.202 | 0.2785 | 0.4146 | 0.4664 | 0.428 | 0.6148 | 0.6627 | 0.6065 | 0.7018 | 0.5 |
| 6.1381 | 45.0 | 14085 | 9.2842 | 0.3692 | 0.8998 | 0.2041 | 0.279 | 0.4205 | 0.4663 | 0.4279 | 0.6116 | 0.6625 | 0.6074 | 0.7012 | 0.4667 |
| 6.1381 | 46.0 | 14398 | 9.2333 | 0.3686 | 0.8987 | 0.2006 | 0.2758 | 0.4211 | 0.4663 | 0.428 | 0.6155 | 0.6621 | 0.6095 | 0.699 | 0.4667 |
| 6.0162 | 47.0 | 14711 | 9.2259 | 0.366 | 0.9051 | 0.1986 | 0.2756 | 0.4155 | 0.4663 | 0.4245 | 0.6157 | 0.6641 | 0.6128 | 0.7002 | 0.4667 |
| 5.9406 | 48.0 | 15024 | 9.2568 | 0.3632 | 0.902 | 0.1941 | 0.2729 | 0.4133 | 0.4733 | 0.4198 | 0.6145 | 0.6623 | 0.606 | 0.7014 | 0.5333 |
| 5.9406 | 49.0 | 15337 | 9.2850 | 0.3635 | 0.904 | 0.196 | 0.2733 | 0.4147 | 0.479 | 0.4223 | 0.616 | 0.6669 | 0.6134 | 0.704 | 0.5333 |
| 5.8549 | 50.0 | 15650 | 9.2647 | 0.3663 | 0.8999 | 0.1997 | 0.2746 | 0.4177 | 0.4663 | 0.4232 | 0.6149 | 0.664 | 0.6107 | 0.7014 | 0.4667 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
|