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detr-v8

Object Detection
Transformers
PyTorch
detr
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +160 -0
  2. config.json +57 -0
  3. preprocessor_config.json +24 -0
  4. pytorch_model.bin +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/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-V8
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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-V8
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+
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+ This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2139
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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: 2e-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: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:------:|:---------------:|
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+ | No log | 0.48 | 1000 | 0.3770 |
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+ | No log | 0.96 | 2000 | 0.3967 |
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+ | 0.4391 | 1.43 | 3000 | 0.3822 |
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+ | 0.4391 | 1.91 | 4000 | 0.4163 |
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+ | 0.4434 | 2.39 | 5000 | 0.3888 |
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+ | 0.4434 | 2.87 | 6000 | 0.3867 |
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+ | 0.4509 | 3.35 | 7000 | 0.4205 |
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+ | 0.4509 | 3.83 | 8000 | 0.4014 |
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+ | 0.455 | 4.3 | 9000 | 0.4117 |
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+ | 0.455 | 4.78 | 10000 | 0.3964 |
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+ | 0.4476 | 5.26 | 11000 | 0.3915 |
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+ | 0.4476 | 5.74 | 12000 | 0.3919 |
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+ | 0.444 | 6.22 | 13000 | 0.4026 |
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+ | 0.444 | 6.7 | 14000 | 0.3832 |
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+ | 0.443 | 7.17 | 15000 | 0.4057 |
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+ | 0.443 | 7.65 | 16000 | 0.3677 |
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+ | 0.4232 | 8.13 | 17000 | 0.3746 |
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+ | 0.4232 | 8.61 | 18000 | 0.3672 |
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+ | 0.4202 | 9.09 | 19000 | 0.3629 |
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+ | 0.4202 | 9.56 | 20000 | 0.3739 |
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+ | 0.4131 | 10.04 | 21000 | 0.3712 |
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+ | 0.4131 | 10.52 | 22000 | 0.3470 |
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+ | 0.4131 | 11.0 | 23000 | 0.3632 |
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+ | 0.4024 | 11.48 | 24000 | 0.3561 |
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+ | 0.4024 | 11.96 | 25000 | 0.3562 |
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+ | 0.4013 | 12.43 | 26000 | 0.3253 |
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+ | 0.4013 | 12.91 | 27000 | 0.3390 |
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+ | 0.3925 | 13.39 | 28000 | 0.3398 |
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+ | 0.3925 | 13.87 | 29000 | 0.3460 |
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+ | 0.3804 | 14.35 | 30000 | 0.3338 |
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+ | 0.3804 | 14.83 | 31000 | 0.3201 |
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+ | 0.3757 | 15.3 | 32000 | 0.3119 |
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+ | 0.3757 | 15.78 | 33000 | 0.3106 |
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+ | 0.3663 | 16.26 | 34000 | 0.3164 |
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+ | 0.3663 | 16.74 | 35000 | 0.3190 |
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+ | 0.3588 | 17.22 | 36000 | 0.3141 |
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+ | 0.3588 | 17.69 | 37000 | 0.3262 |
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+ | 0.3515 | 18.17 | 38000 | 0.3027 |
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+ | 0.3515 | 18.65 | 39000 | 0.3178 |
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+ | 0.3557 | 19.13 | 40000 | 0.3053 |
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+ | 0.3557 | 19.61 | 41000 | 0.3032 |
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+ | 0.3478 | 20.09 | 42000 | 0.3147 |
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+ | 0.3478 | 20.56 | 43000 | 0.3069 |
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+ | 0.3451 | 21.04 | 44000 | 0.3070 |
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+ | 0.3451 | 21.52 | 45000 | 0.3055 |
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+ | 0.3451 | 22.0 | 46000 | 0.2883 |
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+ | 0.3367 | 22.48 | 47000 | 0.3090 |
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+ | 0.3367 | 22.96 | 48000 | 0.2906 |
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+ | 0.3348 | 23.43 | 49000 | 0.2805 |
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+ | 0.3348 | 23.91 | 50000 | 0.2920 |
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+ | 0.3298 | 24.39 | 51000 | 0.2854 |
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+ | 0.3298 | 24.87 | 52000 | 0.2841 |
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+ | 0.3254 | 25.35 | 53000 | 0.2822 |
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+ | 0.3254 | 25.82 | 54000 | 0.2716 |
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+ | 0.3169 | 26.3 | 55000 | 0.2825 |
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+ | 0.3169 | 26.78 | 56000 | 0.2700 |
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+ | 0.314 | 27.26 | 57000 | 0.2640 |
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+ | 0.314 | 27.74 | 58000 | 0.2728 |
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+ | 0.3047 | 28.22 | 59000 | 0.2654 |
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+ | 0.3047 | 28.69 | 60000 | 0.2691 |
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+ | 0.2999 | 29.17 | 61000 | 0.2601 |
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+ | 0.2999 | 29.65 | 62000 | 0.2607 |
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+ | 0.297 | 30.13 | 63000 | 0.2581 |
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+ | 0.297 | 30.61 | 64000 | 0.2511 |
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+ | 0.2946 | 31.09 | 65000 | 0.2557 |
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+ | 0.2946 | 31.56 | 66000 | 0.2568 |
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+ | 0.2912 | 32.04 | 67000 | 0.2569 |
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+ | 0.2912 | 32.52 | 68000 | 0.2594 |
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+ | 0.2912 | 33.0 | 69000 | 0.2553 |
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+ | 0.2906 | 33.48 | 70000 | 0.2425 |
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+ | 0.2906 | 33.96 | 71000 | 0.2475 |
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+ | 0.2833 | 34.43 | 72000 | 0.2394 |
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+ | 0.2833 | 34.91 | 73000 | 0.2422 |
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+ | 0.278 | 35.39 | 74000 | 0.2403 |
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+ | 0.278 | 35.87 | 75000 | 0.2349 |
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+ | 0.2738 | 36.35 | 76000 | 0.2300 |
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+ | 0.2738 | 36.82 | 77000 | 0.2332 |
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+ | 0.2701 | 37.3 | 78000 | 0.2309 |
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+ | 0.2701 | 37.78 | 79000 | 0.2298 |
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+ | 0.2659 | 38.26 | 80000 | 0.2343 |
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+ | 0.2659 | 38.74 | 81000 | 0.2265 |
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+ | 0.2626 | 39.22 | 82000 | 0.2310 |
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+ | 0.2626 | 39.69 | 83000 | 0.2255 |
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+ | 0.259 | 40.17 | 84000 | 0.2263 |
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+ | 0.259 | 40.65 | 85000 | 0.2282 |
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+ | 0.2563 | 41.13 | 86000 | 0.2309 |
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+ | 0.2563 | 41.61 | 87000 | 0.2270 |
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+ | 0.2548 | 42.09 | 88000 | 0.2237 |
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+ | 0.2548 | 42.56 | 89000 | 0.2203 |
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+ | 0.254 | 43.04 | 90000 | 0.2204 |
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+ | 0.254 | 43.52 | 91000 | 0.2218 |
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+ | 0.254 | 44.0 | 92000 | 0.2207 |
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+ | 0.2484 | 44.48 | 93000 | 0.2144 |
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+ | 0.2484 | 44.95 | 94000 | 0.2194 |
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+ | 0.2475 | 45.43 | 95000 | 0.2165 |
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+ | 0.2475 | 45.91 | 96000 | 0.2162 |
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+ | 0.2453 | 46.39 | 97000 | 0.2136 |
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+ | 0.2453 | 46.87 | 98000 | 0.2152 |
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+ | 0.2441 | 47.35 | 99000 | 0.2162 |
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+ | 0.2441 | 47.82 | 100000 | 0.2171 |
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+ | 0.2408 | 48.3 | 101000 | 0.2119 |
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+ | 0.2408 | 48.78 | 102000 | 0.2131 |
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+ | 0.2389 | 49.26 | 103000 | 0.2109 |
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+ | 0.2389 | 49.74 | 104000 | 0.2139 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_commit_hash": "480370a8aeeed9fc8d78837b4e94e5f936fe73f2",
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+ "_name_or_path": "facebook/detr-resnet-50",
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+ "activation_dropout": 0.0,
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+ "activation_function": "relu",
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+ "architectures": [
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+ "DetrForObjectDetection"
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+ ],
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+ "attention_dropout": 0.0,
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+ "auxiliary_loss": false,
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+ "backbone": "resnet50",
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+ "backbone_config": null,
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+ "bbox_cost": 5,
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+ "bbox_loss_coefficient": 5,
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+ "class_cost": 1,
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+ "classifier_dropout": 0.0,
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+ "d_model": 256,
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+ "decoder_attention_heads": 8,
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+ "decoder_ffn_dim": 2048,
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+ "decoder_layerdrop": 0.0,
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+ "decoder_layers": 6,
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+ "dice_loss_coefficient": 1,
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+ "dilation": false,
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+ "dropout": 0.1,
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+ "encoder_attention_heads": 8,
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+ "encoder_ffn_dim": 2048,
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+ "encoder_layerdrop": 0.0,
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+ "encoder_layers": 6,
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+ "eos_coefficient": 0.1,
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+ "giou_cost": 2,
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+ "giou_loss_coefficient": 2,
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+ "id2label": {
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+ "0": "block",
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+ "1": "footer",
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+ "2": "header"
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+ },
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+ "init_std": 0.02,
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+ "init_xavier_std": 1.0,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "block": 0,
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+ "footer": 1,
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+ "header": 2
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+ },
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+ "mask_loss_coefficient": 1,
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+ "max_position_embeddings": 1024,
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+ "model_type": "detr",
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+ "num_channels": 3,
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+ "num_hidden_layers": 6,
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+ "num_queries": 100,
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+ "position_embedding_type": "sine",
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+ "scale_embedding": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.7.0.dev0",
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+ "use_pretrained_backbone": true,
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+ "use_timm_backbone": true
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+ }
preprocessor_config.json ADDED
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+ {
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+ "do_normalize": true,
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+ "do_pad": true,
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+ "do_rescale": true,
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+ "do_resize": true,
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+ "format": "coco_detection",
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+ "image_mean": [
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+ 0.485,
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+ 0.456,
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+ 0.406
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+ ],
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+ "image_processor_type": "DetrImageProcessor",
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+ "image_std": [
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+ 0.229,
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+ 0.224,
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+ 0.225
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+ ],
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+ "resample": 2,
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+ "rescale_factor": 0.00392156862745098,
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+ "size": {
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+ "longest_edge": 1333,
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+ "shortest_edge": 800
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+ }
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+ }
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