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detr_finetuned_cppe5

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: 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: 1.1909
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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 | 107 | 1.9270 |
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+ | No log | 2.0 | 214 | 1.7725 |
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+ | No log | 3.0 | 321 | 1.6696 |
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+ | No log | 4.0 | 428 | 1.6196 |
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+ | 2.6515 | 5.0 | 535 | 1.5855 |
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+ | 2.6515 | 6.0 | 642 | 1.5091 |
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+ | 2.6515 | 7.0 | 749 | 1.4790 |
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+ | 2.6515 | 8.0 | 856 | 1.4786 |
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+ | 2.6515 | 9.0 | 963 | 1.3819 |
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+ | 1.3311 | 10.0 | 1070 | 1.3668 |
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+ | 1.3311 | 11.0 | 1177 | 1.3966 |
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+ | 1.3311 | 12.0 | 1284 | 1.3492 |
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+ | 1.3311 | 13.0 | 1391 | 1.3223 |
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+ | 1.3311 | 14.0 | 1498 | 1.2781 |
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+ | 1.1672 | 15.0 | 1605 | 1.2749 |
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+ | 1.1672 | 16.0 | 1712 | 1.2671 |
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+ | 1.1672 | 17.0 | 1819 | 1.2488 |
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+ | 1.1672 | 18.0 | 1926 | 1.2500 |
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+ | 1.0429 | 19.0 | 2033 | 1.2274 |
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+ | 1.0429 | 20.0 | 2140 | 1.2308 |
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+ | 1.0429 | 21.0 | 2247 | 1.2249 |
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+ | 1.0429 | 22.0 | 2354 | 1.2157 |
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+ | 1.0429 | 23.0 | 2461 | 1.2147 |
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+ | 0.9595 | 24.0 | 2568 | 1.1956 |
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+ | 0.9595 | 25.0 | 2675 | 1.1880 |
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+ | 0.9595 | 26.0 | 2782 | 1.1912 |
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+ | 0.9595 | 27.0 | 2889 | 1.1916 |
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+ | 0.9595 | 28.0 | 2996 | 1.1921 |
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+ | 0.9097 | 29.0 | 3103 | 1.1912 |
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+ | 0.9097 | 30.0 | 3210 | 1.1909 |
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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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