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detr_finetuned_cppe5

Object Detection
Transformers
Safetensors
conditional_detr
Generated from Trainer
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/conditional-detr-resnet-50
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: detr_finetuned_cppe5
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # detr_finetuned_cppe5
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+
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+ This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.9593
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+ - Map: 0.0044
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+ - Map 50: 0.0137
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+ - Map 75: 0.0023
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+ - Map Small: 0.0022
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+ - Map Medium: 0.0004
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+ - Map Large: 0.0048
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+ - Mar 1: 0.0129
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+ - Mar 10: 0.0353
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+ - Mar 100: 0.0591
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+ - Mar Small: 0.0018
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+ - Mar Medium: 0.0246
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+ - Mar Large: 0.0575
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+ - Map Coverall: 0.0207
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+ - Mar 100 Coverall: 0.2338
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+ - Map Face Shield: 0.0001
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+ - Mar 100 Face Shield: 0.0038
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+ - Map Gloves: 0.0002
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+ - Mar 100 Gloves: 0.021
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+ - Map Goggles: 0.0
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+ - Mar 100 Goggles: 0.0
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+ - Map Mask: 0.001
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+ - Mar 100 Mask: 0.0369
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | 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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
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+ | No log | 1.0 | 107 | 3.4694 | 0.0001 | 0.0007 | 0.0 | 0.0 | 0.0001 | 0.0002 | 0.0018 | 0.0054 | 0.0086 | 0.0057 | 0.0035 | 0.0055 | 0.0004 | 0.0239 | 0.0 | 0.0 | 0.0 | 0.0022 | 0.0 | 0.0 | 0.0001 | 0.0169 |
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+ | No log | 2.0 | 214 | 3.3011 | 0.0009 | 0.0029 | 0.0003 | 0.0009 | 0.0 | 0.0009 | 0.0022 | 0.0183 | 0.0288 | 0.0011 | 0.007 | 0.0292 | 0.0042 | 0.1275 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0164 |
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+ | No log | 3.0 | 321 | 3.4689 | 0.0012 | 0.0045 | 0.0003 | 0.0 | 0.0 | 0.0013 | 0.0032 | 0.0169 | 0.0355 | 0.0 | 0.0 | 0.0406 | 0.0059 | 0.1775 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 4.0 | 428 | 3.2984 | 0.0018 | 0.0077 | 0.0005 | 0.0002 | 0.0001 | 0.0021 | 0.005 | 0.0216 | 0.0346 | 0.0002 | 0.0169 | 0.0316 | 0.009 | 0.1383 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0347 |
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+ | 4.926 | 5.0 | 535 | 3.1808 | 0.0019 | 0.0071 | 0.0005 | 0.0002 | 0.0001 | 0.0021 | 0.0032 | 0.0229 | 0.0445 | 0.0002 | 0.0157 | 0.0431 | 0.0093 | 0.1883 | 0.0 | 0.0 | 0.0 | 0.0089 | 0.0 | 0.0 | 0.0001 | 0.0253 |
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+ | 4.926 | 6.0 | 642 | 3.1296 | 0.002 | 0.007 | 0.0007 | 0.0005 | 0.0001 | 0.0022 | 0.0059 | 0.0207 | 0.0487 | 0.0015 | 0.0168 | 0.0477 | 0.0099 | 0.2095 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0342 |
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+ | 4.926 | 7.0 | 749 | 3.1212 | 0.0021 | 0.007 | 0.0007 | 0.0007 | 0.0008 | 0.0024 | 0.0029 | 0.0255 | 0.0505 | 0.0007 | 0.0143 | 0.051 | 0.0104 | 0.2234 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0289 |
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+ | 4.926 | 8.0 | 856 | 3.2044 | 0.0045 | 0.0148 | 0.0014 | 0.0007 | 0.0 | 0.0051 | 0.0095 | 0.0208 | 0.037 | 0.0007 | 0.0108 | 0.0363 | 0.0222 | 0.1586 | 0.0 | 0.0 | 0.0001 | 0.0129 | 0.0 | 0.0 | 0.0 | 0.0133 |
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+ | 4.926 | 9.0 | 963 | 3.1113 | 0.0028 | 0.0104 | 0.0005 | 0.004 | 0.0001 | 0.0032 | 0.0111 | 0.0237 | 0.0436 | 0.0031 | 0.0133 | 0.0421 | 0.014 | 0.1838 | 0.0 | 0.0 | 0.0 | 0.0058 | 0.0 | 0.0 | 0.0002 | 0.0284 |
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+ | 3.0252 | 10.0 | 1070 | 3.1235 | 0.0038 | 0.0142 | 0.0013 | 0.0013 | 0.0 | 0.0039 | 0.0039 | 0.0283 | 0.0506 | 0.0016 | 0.007 | 0.0534 | 0.0167 | 0.2333 | 0.0 | 0.0 | 0.0 | 0.0107 | 0.0 | 0.0 | 0.0021 | 0.0089 |
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+ | 3.0252 | 11.0 | 1177 | 3.0521 | 0.0041 | 0.0136 | 0.0015 | 0.0062 | 0.0 | 0.0042 | 0.0121 | 0.0309 | 0.051 | 0.0062 | 0.0081 | 0.0514 | 0.0185 | 0.2248 | 0.0 | 0.0 | 0.0001 | 0.0071 | 0.0 | 0.0 | 0.0018 | 0.0231 |
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+ | 3.0252 | 12.0 | 1284 | 3.1122 | 0.0026 | 0.0087 | 0.0008 | 0.001 | 0.0016 | 0.0029 | 0.0084 | 0.0284 | 0.0496 | 0.0005 | 0.0128 | 0.05 | 0.013 | 0.2194 | 0.0 | 0.0 | 0.0001 | 0.0205 | 0.0 | 0.0 | 0.0 | 0.008 |
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+ | 3.0252 | 13.0 | 1391 | 3.1495 | 0.0028 | 0.0096 | 0.0005 | 0.0 | 0.0001 | 0.0031 | 0.0082 | 0.0285 | 0.0481 | 0.0 | 0.0173 | 0.0459 | 0.0136 | 0.2005 | 0.0 | 0.0 | 0.0001 | 0.0219 | 0.0 | 0.0 | 0.0001 | 0.0182 |
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+ | 3.0252 | 14.0 | 1498 | 3.1443 | 0.0026 | 0.0083 | 0.0006 | 0.0 | 0.0001 | 0.0029 | 0.0091 | 0.0253 | 0.0486 | 0.0 | 0.0155 | 0.0466 | 0.0127 | 0.2036 | 0.0 | 0.0 | 0.0002 | 0.0344 | 0.0 | 0.0 | 0.0 | 0.0049 |
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+ | 2.9223 | 15.0 | 1605 | 3.0269 | 0.0064 | 0.0181 | 0.0035 | 0.0035 | 0.0001 | 0.0072 | 0.0109 | 0.0318 | 0.0494 | 0.0029 | 0.012 | 0.0491 | 0.0314 | 0.2144 | 0.0 | 0.0 | 0.0001 | 0.0112 | 0.0 | 0.0 | 0.0002 | 0.0213 |
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+ | 2.9223 | 16.0 | 1712 | 3.0312 | 0.0068 | 0.0178 | 0.0048 | 0.0015 | 0.0004 | 0.0077 | 0.0122 | 0.0323 | 0.0469 | 0.0013 | 0.0215 | 0.0419 | 0.033 | 0.1829 | 0.0 | 0.0 | 0.0002 | 0.0241 | 0.0 | 0.0 | 0.0008 | 0.0276 |
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+ | 2.9223 | 17.0 | 1819 | 2.9839 | 0.0055 | 0.0158 | 0.0026 | 0.0027 | 0.0002 | 0.006 | 0.0118 | 0.0308 | 0.0527 | 0.0022 | 0.0236 | 0.0472 | 0.0267 | 0.2063 | 0.0 | 0.0 | 0.0001 | 0.0214 | 0.0 | 0.0 | 0.0006 | 0.0356 |
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+ | 2.9223 | 18.0 | 1926 | 3.0200 | 0.0064 | 0.0186 | 0.0036 | 0.0005 | 0.0004 | 0.0072 | 0.0118 | 0.0295 | 0.0519 | 0.0004 | 0.0298 | 0.044 | 0.0311 | 0.1923 | 0.0 | 0.0 | 0.0001 | 0.0263 | 0.0 | 0.0 | 0.0008 | 0.0409 |
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+ | 2.8252 | 19.0 | 2033 | 2.9895 | 0.0053 | 0.0166 | 0.0029 | 0.0025 | 0.0002 | 0.006 | 0.0113 | 0.0292 | 0.0475 | 0.002 | 0.021 | 0.0428 | 0.0262 | 0.1869 | 0.0 | 0.0 | 0.0001 | 0.0188 | 0.0 | 0.0 | 0.0004 | 0.032 |
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+ | 2.8252 | 20.0 | 2140 | 3.0483 | 0.0038 | 0.0124 | 0.0018 | 0.0002 | 0.0001 | 0.0044 | 0.0111 | 0.0275 | 0.0431 | 0.0002 | 0.0172 | 0.0403 | 0.0188 | 0.1761 | 0.0 | 0.0 | 0.0001 | 0.0174 | 0.0 | 0.0 | 0.0002 | 0.0218 |
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+ | 2.8252 | 21.0 | 2247 | 3.0509 | 0.0035 | 0.0112 | 0.0017 | 0.0 | 0.0001 | 0.004 | 0.0102 | 0.0314 | 0.0547 | 0.0 | 0.0124 | 0.0563 | 0.0174 | 0.2459 | 0.0 | 0.0 | 0.0 | 0.0107 | 0.0 | 0.0 | 0.0001 | 0.0169 |
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+ | 2.8252 | 22.0 | 2354 | 2.9868 | 0.0039 | 0.0136 | 0.0015 | 0.001 | 0.0004 | 0.0042 | 0.0117 | 0.0353 | 0.064 | 0.0007 | 0.0304 | 0.0576 | 0.0183 | 0.2518 | 0.0 | 0.0 | 0.0001 | 0.0232 | 0.0 | 0.0 | 0.0009 | 0.0449 |
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+ | 2.8252 | 23.0 | 2461 | 2.9752 | 0.0042 | 0.0137 | 0.0019 | 0.0015 | 0.0002 | 0.0047 | 0.0112 | 0.0337 | 0.0601 | 0.0011 | 0.021 | 0.0575 | 0.0204 | 0.2514 | 0.0 | 0.0 | 0.0002 | 0.0188 | 0.0 | 0.0 | 0.0004 | 0.0302 |
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+ | 2.803 | 24.0 | 2568 | 2.9948 | 0.0042 | 0.013 | 0.0021 | 0.0015 | 0.0002 | 0.0046 | 0.0109 | 0.0309 | 0.0557 | 0.0011 | 0.0212 | 0.0526 | 0.0203 | 0.2297 | 0.0 | 0.0 | 0.0001 | 0.0174 | 0.0 | 0.0 | 0.0004 | 0.0316 |
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+ | 2.803 | 25.0 | 2675 | 2.9797 | 0.0043 | 0.0139 | 0.0016 | 0.0015 | 0.0004 | 0.0047 | 0.0119 | 0.033 | 0.059 | 0.0011 | 0.0255 | 0.0541 | 0.0204 | 0.2365 | 0.0 | 0.0 | 0.0001 | 0.0214 | 0.0 | 0.0 | 0.001 | 0.0373 |
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+ | 2.803 | 26.0 | 2782 | 2.9674 | 0.0042 | 0.0133 | 0.0022 | 0.002 | 0.0003 | 0.0046 | 0.0117 | 0.0336 | 0.0579 | 0.0017 | 0.0229 | 0.054 | 0.0201 | 0.236 | 0.0 | 0.0 | 0.0002 | 0.0152 | 0.0 | 0.0 | 0.0008 | 0.0382 |
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+ | 2.803 | 27.0 | 2889 | 2.9539 | 0.0044 | 0.0141 | 0.0021 | 0.0025 | 0.0003 | 0.0047 | 0.012 | 0.0352 | 0.0592 | 0.0021 | 0.0232 | 0.0552 | 0.0207 | 0.241 | 0.0 | 0.0 | 0.0002 | 0.0192 | 0.0 | 0.0 | 0.0009 | 0.036 |
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+ | 2.803 | 28.0 | 2996 | 2.9604 | 0.0042 | 0.0135 | 0.0021 | 0.002 | 0.0004 | 0.0046 | 0.0128 | 0.0347 | 0.0587 | 0.0016 | 0.0239 | 0.0575 | 0.0199 | 0.2338 | 0.0001 | 0.0038 | 0.0002 | 0.0205 | 0.0 | 0.0 | 0.0009 | 0.0356 |
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+ | 2.7833 | 29.0 | 3103 | 2.9589 | 0.0044 | 0.0137 | 0.0023 | 0.0022 | 0.0004 | 0.0048 | 0.0129 | 0.035 | 0.0592 | 0.0018 | 0.0244 | 0.0577 | 0.0207 | 0.2347 | 0.0001 | 0.0038 | 0.0002 | 0.0205 | 0.0 | 0.0 | 0.001 | 0.0369 |
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+ | 2.7833 | 30.0 | 3210 | 2.9593 | 0.0044 | 0.0137 | 0.0023 | 0.0022 | 0.0004 | 0.0048 | 0.0129 | 0.0353 | 0.0591 | 0.0018 | 0.0246 | 0.0575 | 0.0207 | 0.2338 | 0.0001 | 0.0038 | 0.0002 | 0.021 | 0.0 | 0.0 | 0.001 | 0.0369 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.2.2
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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