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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-resnet-50_finetuned_swny |
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results: [] |
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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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# detr-resnet-50_finetuned_swny |
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/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: 1.7504 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 5.6587 | 4.7619 | 100 | 5.5964 | |
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| 4.3793 | 9.5238 | 200 | 3.8578 | |
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| 3.4828 | 14.2857 | 300 | 3.2121 | |
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| 2.8371 | 19.0476 | 400 | 2.6974 | |
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| 2.3745 | 23.8095 | 500 | 2.3697 | |
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| 2.0983 | 28.5714 | 600 | 2.0374 | |
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| 1.995 | 33.3333 | 700 | 2.0759 | |
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| 1.8153 | 38.0952 | 800 | 1.9295 | |
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| 1.7984 | 42.8571 | 900 | 1.8945 | |
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| 1.6725 | 47.6190 | 1000 | 1.8271 | |
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| 1.5961 | 52.3810 | 1100 | 1.8709 | |
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| 1.5454 | 57.1429 | 1200 | 1.8674 | |
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| 1.4977 | 61.9048 | 1300 | 1.8333 | |
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| 1.4575 | 66.6667 | 1400 | 1.8387 | |
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| 1.4784 | 71.4286 | 1500 | 1.8334 | |
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| 1.4698 | 76.1905 | 1600 | 1.7419 | |
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| 1.4335 | 80.9524 | 1700 | 1.8332 | |
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| 1.394 | 85.7143 | 1800 | 1.8329 | |
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| 1.3992 | 90.4762 | 1900 | 1.7304 | |
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| 1.3951 | 95.2381 | 2000 | 1.6899 | |
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| 1.3984 | 100.0 | 2100 | 1.7504 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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