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---
library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr_domain_shift
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. -->
# detr_domain_shift
This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4246
- Map: 0.8353
- Map 50: 0.9529
- Map 75: 0.9029
- Map Small: 0.0159
- Map Medium: 0.6742
- Map Large: 0.8707
- Mar 1: 0.7106
- Mar 10: 0.8977
- Mar 100: 0.9152
- Mar Small: 0.2984
- Mar Medium: 0.8276
- Mar Large: 0.9365
- Map Garbage bag: 0.8185
- Mar 100 Garbage bag: 0.9059
- Map Paper bag: 0.8446
- Mar 100 Paper bag: 0.9239
- Map Plastic bag: 0.8429
- Mar 100 Plastic bag: 0.9159
## 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: 0.0001
- train_batch_size: 8
- 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: cosine
- 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 | Map Garbage bag | Mar 100 Garbage bag | Map Paper bag | Mar 100 Paper bag | Map Plastic bag | Mar 100 Plastic bag |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------------:|:-------------------:|:-------------:|:-----------------:|:---------------:|:-------------------:|
| 0.9775 | 1.0 | 1557 | 0.8739 | 0.2419 | 0.3276 | 0.2719 | 0.0003 | 0.1808 | 0.2566 | 0.4246 | 0.773 | 0.8186 | 0.0271 | 0.6849 | 0.8501 | 0.1999 | 0.808 | 0.3045 | 0.8292 | 0.2213 | 0.8187 |
| 0.919 | 2.0 | 3114 | 0.8527 | 0.4465 | 0.6037 | 0.5018 | 0.0043 | 0.2877 | 0.4787 | 0.5098 | 0.7627 | 0.8137 | 0.0123 | 0.6656 | 0.8474 | 0.5496 | 0.8075 | 0.4518 | 0.8235 | 0.3382 | 0.8101 |
| 0.85 | 3.0 | 4671 | 0.7649 | 0.5508 | 0.7268 | 0.6183 | 0.0013 | 0.3684 | 0.5898 | 0.5619 | 0.7944 | 0.8335 | 0.0652 | 0.7147 | 0.8613 | 0.5635 | 0.8206 | 0.5877 | 0.8471 | 0.5012 | 0.8327 |
| 0.844 | 4.0 | 6228 | 0.7562 | 0.605 | 0.7924 | 0.6857 | 0.0023 | 0.4402 | 0.6405 | 0.5732 | 0.7901 | 0.8296 | 0.0579 | 0.7174 | 0.856 | 0.6113 | 0.8213 | 0.6125 | 0.8364 | 0.5912 | 0.8313 |
| 0.8332 | 5.0 | 7785 | 0.7811 | 0.5982 | 0.8004 | 0.6799 | 0.007 | 0.4141 | 0.6365 | 0.5683 | 0.7801 | 0.8214 | 0.0194 | 0.6914 | 0.852 | 0.5785 | 0.8091 | 0.6326 | 0.8361 | 0.5834 | 0.8188 |
| 0.9303 | 6.0 | 9342 | 0.9325 | 0.5179 | 0.7395 | 0.5906 | 0.0001 | 0.3665 | 0.5506 | 0.5192 | 0.7288 | 0.7756 | 0.0097 | 0.6358 | 0.8074 | 0.52 | 0.7664 | 0.5744 | 0.7825 | 0.4593 | 0.7778 |
| 0.8773 | 7.0 | 10899 | 0.8869 | 0.5561 | 0.7748 | 0.626 | 0.0 | 0.374 | 0.5948 | 0.547 | 0.748 | 0.7895 | 0.0 | 0.6483 | 0.8223 | 0.5435 | 0.7752 | 0.5909 | 0.8132 | 0.5339 | 0.7801 |
| 1.011 | 8.0 | 12456 | 0.8729 | 0.5604 | 0.7945 | 0.6437 | 0.0013 | 0.3991 | 0.5954 | 0.538 | 0.7475 | 0.7971 | 0.0218 | 0.6489 | 0.831 | 0.5251 | 0.7729 | 0.6152 | 0.8222 | 0.541 | 0.7962 |
| 1.0019 | 9.0 | 14013 | 1.2187 | 0.313 | 0.5258 | 0.3396 | 0.0 | 0.2026 | 0.337 | 0.3859 | 0.6118 | 0.6892 | 0.0 | 0.5141 | 0.7282 | 0.4395 | 0.7076 | 0.2496 | 0.6916 | 0.25 | 0.6685 |
| 0.9286 | 10.0 | 15570 | 0.8059 | 0.5848 | 0.7852 | 0.6584 | 0.0 | 0.3874 | 0.6257 | 0.5595 | 0.7725 | 0.8196 | 0.0179 | 0.6689 | 0.8539 | 0.5762 | 0.8015 | 0.6239 | 0.8429 | 0.5544 | 0.8143 |
| 0.8782 | 11.0 | 17127 | 0.8458 | 0.5587 | 0.7551 | 0.627 | 0.01 | 0.377 | 0.596 | 0.5551 | 0.7678 | 0.812 | 0.0516 | 0.6635 | 0.8453 | 0.5726 | 0.7966 | 0.6164 | 0.8355 | 0.4872 | 0.804 |
| 0.8493 | 12.0 | 18684 | 0.7872 | 0.5899 | 0.7787 | 0.6622 | 0.0012 | 0.3803 | 0.6329 | 0.57 | 0.7832 | 0.8287 | 0.019 | 0.6719 | 0.8643 | 0.5813 | 0.8215 | 0.6336 | 0.8412 | 0.5548 | 0.8235 |
| 0.793 | 13.0 | 20241 | 0.7784 | 0.6112 | 0.8128 | 0.6924 | 0.0023 | 0.4275 | 0.6502 | 0.5785 | 0.7783 | 0.8249 | 0.0434 | 0.6872 | 0.8566 | 0.6157 | 0.8253 | 0.6326 | 0.8344 | 0.5852 | 0.8151 |
| 0.7712 | 14.0 | 21798 | 0.7881 | 0.6089 | 0.8162 | 0.688 | 0.0001 | 0.4211 | 0.6497 | 0.5772 | 0.7785 | 0.8184 | 0.039 | 0.6874 | 0.8491 | 0.5984 | 0.803 | 0.6429 | 0.84 | 0.5853 | 0.8123 |
| 0.7892 | 15.0 | 23355 | 0.7204 | 0.6548 | 0.8515 | 0.742 | 0.0007 | 0.486 | 0.6916 | 0.6018 | 0.7991 | 0.8376 | 0.0359 | 0.7139 | 0.8668 | 0.653 | 0.8377 | 0.6716 | 0.8447 | 0.6399 | 0.8302 |
| 0.7735 | 16.0 | 24912 | 0.7768 | 0.604 | 0.7908 | 0.6807 | 0.0152 | 0.4142 | 0.6445 | 0.5803 | 0.7794 | 0.8258 | 0.043 | 0.7167 | 0.8522 | 0.5854 | 0.8359 | 0.6421 | 0.8307 | 0.5844 | 0.8106 |
| 0.8052 | 17.0 | 26469 | 0.7466 | 0.6389 | 0.8417 | 0.7325 | 0.0001 | 0.4658 | 0.6767 | 0.5883 | 0.7847 | 0.8231 | 0.0245 | 0.7291 | 0.8469 | 0.6493 | 0.8262 | 0.6572 | 0.8329 | 0.6101 | 0.8101 |
| 0.7366 | 18.0 | 28026 | 0.7490 | 0.6372 | 0.8435 | 0.7198 | 0.0069 | 0.4492 | 0.6783 | 0.5883 | 0.7881 | 0.8287 | 0.0271 | 0.7084 | 0.8572 | 0.6427 | 0.8307 | 0.6486 | 0.8376 | 0.6202 | 0.8178 |
| 0.7316 | 19.0 | 29583 | 0.6964 | 0.6697 | 0.869 | 0.7578 | 0.0028 | 0.5095 | 0.704 | 0.6068 | 0.8029 | 0.839 | 0.0705 | 0.7283 | 0.8651 | 0.6529 | 0.8277 | 0.6915 | 0.8538 | 0.6646 | 0.8353 |
| 0.7243 | 20.0 | 31140 | 0.7165 | 0.6616 | 0.8605 | 0.753 | 0.0033 | 0.4782 | 0.7003 | 0.6046 | 0.7972 | 0.8299 | 0.0581 | 0.7148 | 0.8574 | 0.6366 | 0.8126 | 0.6791 | 0.8452 | 0.6692 | 0.832 |
| 0.7189 | 21.0 | 32697 | 0.6921 | 0.6748 | 0.8694 | 0.7621 | 0.001 | 0.5019 | 0.7121 | 0.6105 | 0.8042 | 0.8382 | 0.0788 | 0.7253 | 0.8649 | 0.6422 | 0.8241 | 0.7087 | 0.8581 | 0.6735 | 0.8324 |
| 0.6802 | 22.0 | 34254 | 0.6381 | 0.7091 | 0.886 | 0.7875 | 0.0007 | 0.5366 | 0.7465 | 0.6318 | 0.8291 | 0.8618 | 0.0716 | 0.752 | 0.8883 | 0.6953 | 0.8572 | 0.7253 | 0.8718 | 0.7067 | 0.8565 |
| 0.6676 | 23.0 | 35811 | 0.6252 | 0.7186 | 0.8865 | 0.7994 | 0.0034 | 0.5423 | 0.7573 | 0.6391 | 0.8373 | 0.8649 | 0.0665 | 0.7597 | 0.8908 | 0.7021 | 0.8567 | 0.7358 | 0.8752 | 0.7181 | 0.8628 |
| 0.6624 | 24.0 | 37368 | 0.6432 | 0.7117 | 0.8986 | 0.8041 | 0.0019 | 0.5384 | 0.7488 | 0.63 | 0.8205 | 0.8535 | 0.0974 | 0.7492 | 0.8786 | 0.6871 | 0.8394 | 0.7287 | 0.8639 | 0.7194 | 0.8572 |
| 0.6356 | 25.0 | 38925 | 0.6101 | 0.7284 | 0.905 | 0.8178 | 0.004 | 0.5444 | 0.7676 | 0.6448 | 0.8322 | 0.863 | 0.1108 | 0.7616 | 0.8874 | 0.7125 | 0.8556 | 0.7417 | 0.8709 | 0.7311 | 0.8626 |
| 0.6319 | 26.0 | 40482 | 0.6330 | 0.7191 | 0.9005 | 0.8113 | 0.0085 | 0.557 | 0.754 | 0.6392 | 0.8262 | 0.8513 | 0.106 | 0.7566 | 0.8745 | 0.702 | 0.849 | 0.7371 | 0.8558 | 0.7182 | 0.8489 |
| 0.6069 | 27.0 | 42039 | 0.5855 | 0.7461 | 0.9072 | 0.824 | 0.0082 | 0.5615 | 0.7852 | 0.6512 | 0.845 | 0.8742 | 0.2484 | 0.7625 | 0.9003 | 0.7159 | 0.8596 | 0.7615 | 0.884 | 0.7609 | 0.8791 |
| 0.5898 | 28.0 | 43596 | 0.5582 | 0.7581 | 0.9158 | 0.8405 | 0.0091 | 0.5844 | 0.7957 | 0.6649 | 0.8552 | 0.878 | 0.2474 | 0.785 | 0.9008 | 0.7384 | 0.8677 | 0.7742 | 0.8882 | 0.7616 | 0.8782 |
| 0.5777 | 29.0 | 45153 | 0.5412 | 0.7706 | 0.9226 | 0.8492 | 0.0029 | 0.6117 | 0.8054 | 0.6718 | 0.8591 | 0.8878 | 0.2147 | 0.7882 | 0.9118 | 0.7542 | 0.8826 | 0.7799 | 0.8953 | 0.7777 | 0.8854 |
| 0.5461 | 30.0 | 46710 | 0.5424 | 0.7714 | 0.9259 | 0.8563 | 0.0024 | 0.6033 | 0.8081 | 0.6708 | 0.8571 | 0.8829 | 0.206 | 0.7823 | 0.9069 | 0.7602 | 0.8784 | 0.7814 | 0.8906 | 0.7726 | 0.8798 |
| 0.5392 | 31.0 | 48267 | 0.5274 | 0.7773 | 0.9219 | 0.8591 | 0.0026 | 0.5986 | 0.8159 | 0.6752 | 0.8648 | 0.8888 | 0.2832 | 0.795 | 0.9111 | 0.7549 | 0.8835 | 0.7902 | 0.894 | 0.7867 | 0.8889 |
| 0.5367 | 32.0 | 49824 | 0.5181 | 0.7863 | 0.9312 | 0.8654 | 0.0038 | 0.6234 | 0.8216 | 0.678 | 0.8663 | 0.8882 | 0.2332 | 0.7956 | 0.9109 | 0.7689 | 0.8805 | 0.7985 | 0.8962 | 0.7915 | 0.8879 |
| 0.5187 | 33.0 | 51381 | 0.5079 | 0.7853 | 0.934 | 0.8672 | 0.0187 | 0.6245 | 0.8206 | 0.6814 | 0.8681 | 0.8917 | 0.2412 | 0.7984 | 0.9143 | 0.7692 | 0.89 | 0.7937 | 0.8966 | 0.7931 | 0.8884 |
| 0.5102 | 34.0 | 52938 | 0.4861 | 0.8049 | 0.9381 | 0.8761 | 0.0318 | 0.6481 | 0.8388 | 0.6912 | 0.8811 | 0.9047 | 0.2659 | 0.818 | 0.9262 | 0.7893 | 0.8991 | 0.8191 | 0.914 | 0.8062 | 0.901 |
| 0.4868 | 35.0 | 54495 | 0.4753 | 0.8046 | 0.9392 | 0.8827 | 0.0084 | 0.6389 | 0.8413 | 0.6933 | 0.8796 | 0.9015 | 0.2495 | 0.8056 | 0.9249 | 0.7884 | 0.8981 | 0.811 | 0.9036 | 0.8143 | 0.903 |
| 0.4821 | 36.0 | 56052 | 0.4714 | 0.8096 | 0.9427 | 0.8861 | 0.0225 | 0.6485 | 0.8448 | 0.6955 | 0.8828 | 0.9042 | 0.278 | 0.8159 | 0.9258 | 0.7923 | 0.8981 | 0.8221 | 0.9121 | 0.8143 | 0.9024 |
| 0.4714 | 37.0 | 57609 | 0.4447 | 0.8232 | 0.9433 | 0.8911 | 0.0219 | 0.6619 | 0.8599 | 0.7032 | 0.8935 | 0.9126 | 0.269 | 0.8235 | 0.9344 | 0.8072 | 0.9051 | 0.8295 | 0.9173 | 0.8329 | 0.9154 |
| 0.4653 | 38.0 | 59166 | 0.4554 | 0.819 | 0.946 | 0.8912 | 0.0178 | 0.6567 | 0.8548 | 0.7021 | 0.8873 | 0.9059 | 0.3004 | 0.8138 | 0.9281 | 0.8025 | 0.899 | 0.8281 | 0.9122 | 0.8264 | 0.9065 |
| 0.4494 | 39.0 | 60723 | 0.4310 | 0.8308 | 0.9451 | 0.8939 | 0.0243 | 0.6685 | 0.8663 | 0.7091 | 0.8985 | 0.918 | 0.3242 | 0.8358 | 0.9381 | 0.8127 | 0.9114 | 0.8401 | 0.9237 | 0.8397 | 0.919 |
| 0.4389 | 40.0 | 62280 | 0.4289 | 0.8336 | 0.9489 | 0.8967 | 0.0177 | 0.6757 | 0.8684 | 0.7102 | 0.8976 | 0.9165 | 0.2958 | 0.8329 | 0.9369 | 0.8167 | 0.9102 | 0.8425 | 0.9219 | 0.8416 | 0.9174 |
| 0.4376 | 41.0 | 63837 | 0.4245 | 0.8365 | 0.9498 | 0.9011 | 0.0179 | 0.6795 | 0.8709 | 0.7122 | 0.8985 | 0.9182 | 0.3335 | 0.8382 | 0.9377 | 0.8167 | 0.9067 | 0.8477 | 0.9272 | 0.845 | 0.9205 |
| 0.4252 | 42.0 | 65394 | 0.4244 | 0.8368 | 0.9511 | 0.8998 | 0.0175 | 0.6802 | 0.8713 | 0.7106 | 0.8988 | 0.9166 | 0.3604 | 0.8331 | 0.9369 | 0.8183 | 0.9089 | 0.8467 | 0.9229 | 0.8456 | 0.9179 |
| 0.4215 | 43.0 | 66951 | 0.4281 | 0.8342 | 0.9517 | 0.8987 | 0.0297 | 0.6731 | 0.8696 | 0.7088 | 0.8985 | 0.9159 | 0.3176 | 0.83 | 0.9369 | 0.8177 | 0.9092 | 0.8431 | 0.9217 | 0.8418 | 0.9169 |
| 0.4279 | 44.0 | 68508 | 0.4235 | 0.8375 | 0.9527 | 0.9012 | 0.0191 | 0.6777 | 0.873 | 0.7116 | 0.8984 | 0.9164 | 0.32 | 0.8288 | 0.9376 | 0.8191 | 0.9094 | 0.8479 | 0.9226 | 0.8453 | 0.9172 |
| 0.4133 | 45.0 | 70065 | 0.4220 | 0.837 | 0.9525 | 0.9014 | 0.0168 | 0.6764 | 0.8719 | 0.7117 | 0.9 | 0.9175 | 0.3059 | 0.8353 | 0.9377 | 0.8168 | 0.9081 | 0.8488 | 0.9244 | 0.8455 | 0.9199 |
| 0.4085 | 46.0 | 71622 | 0.4231 | 0.837 | 0.9538 | 0.9026 | 0.0158 | 0.679 | 0.8721 | 0.7118 | 0.8986 | 0.9157 | 0.2905 | 0.8276 | 0.9371 | 0.8196 | 0.908 | 0.8463 | 0.9227 | 0.8451 | 0.9165 |
| 0.4138 | 47.0 | 73179 | 0.4269 | 0.8335 | 0.9529 | 0.9019 | 0.014 | 0.6735 | 0.8689 | 0.7097 | 0.8965 | 0.9141 | 0.2954 | 0.8246 | 0.9358 | 0.8145 | 0.9048 | 0.8436 | 0.9226 | 0.8424 | 0.9149 |
| 0.4147 | 48.0 | 74736 | 0.4246 | 0.8353 | 0.9529 | 0.9023 | 0.0158 | 0.6736 | 0.8709 | 0.7108 | 0.8979 | 0.9155 | 0.2982 | 0.8266 | 0.937 | 0.8182 | 0.9062 | 0.8447 | 0.9242 | 0.843 | 0.916 |
| 0.4145 | 49.0 | 76293 | 0.4237 | 0.8362 | 0.9531 | 0.9027 | 0.0159 | 0.6751 | 0.8715 | 0.7108 | 0.8984 | 0.916 | 0.2984 | 0.8286 | 0.9373 | 0.8192 | 0.9067 | 0.8454 | 0.9248 | 0.8439 | 0.9167 |
| 0.406 | 50.0 | 77850 | 0.4246 | 0.8353 | 0.9529 | 0.9029 | 0.0159 | 0.6742 | 0.8707 | 0.7106 | 0.8977 | 0.9152 | 0.2984 | 0.8276 | 0.9365 | 0.8185 | 0.9059 | 0.8446 | 0.9239 | 0.8429 | 0.9159 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0
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