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cppe5_setup_on_roadsign_test

Object Detection
Transformers
Safetensors
conditional_detr
Generated from Trainer
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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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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: cppe5_setup_on_roadsign_test
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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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+ # cppe5_setup_on_roadsign_test
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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: 0.7737
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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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 35 | 3.7723 |
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+ | No log | 2.0 | 70 | 1.9201 |
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+ | No log | 3.0 | 105 | 1.4291 |
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+ | No log | 4.0 | 140 | 1.3266 |
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+ | No log | 5.0 | 175 | 1.2345 |
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+ | No log | 6.0 | 210 | 1.0995 |
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+ | No log | 7.0 | 245 | 1.0747 |
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+ | No log | 8.0 | 280 | 1.0331 |
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+ | No log | 9.0 | 315 | 0.9756 |
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+ | No log | 10.0 | 350 | 0.9451 |
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+ | No log | 11.0 | 385 | 0.8785 |
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+ | No log | 12.0 | 420 | 0.8856 |
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+ | No log | 13.0 | 455 | 0.8277 |
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+ | No log | 14.0 | 490 | 0.8373 |
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+ | 3.9603 | 15.0 | 525 | 0.8116 |
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+ | 3.9603 | 16.0 | 560 | 0.8188 |
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+ | 3.9603 | 17.0 | 595 | 0.8119 |
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+ | 3.9603 | 18.0 | 630 | 0.7920 |
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+ | 3.9603 | 19.0 | 665 | 0.7772 |
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+ | 3.9603 | 20.0 | 700 | 0.7651 |
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+ | 3.9603 | 21.0 | 735 | 0.7721 |
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+ | 3.9603 | 22.0 | 770 | 0.7944 |
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+ | 3.9603 | 23.0 | 805 | 0.7888 |
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+ | 3.9603 | 24.0 | 840 | 0.7523 |
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+ | 3.9603 | 25.0 | 875 | 0.7697 |
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+ | 3.9603 | 26.0 | 910 | 0.7568 |
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+ | 3.9603 | 27.0 | 945 | 0.7680 |
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+ | 3.9603 | 28.0 | 980 | 0.7712 |
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+ | 0.7588 | 29.0 | 1015 | 0.7740 |
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+ | 0.7588 | 30.0 | 1050 | 0.7737 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.56.2
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+ - Pytorch 2.8.0
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+ - Datasets 4.1.1
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+ - Tokenizers 0.22.1
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