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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-amzss3-v2 |
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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-amzss3-v2 |
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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: 0.3494 |
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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: 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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| No log | 0.54 | 1000 | 0.4810 | |
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| 0.5325 | 1.08 | 2000 | 0.4812 | |
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| 0.5325 | 1.62 | 3000 | 0.4739 | |
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| 0.5322 | 2.16 | 4000 | 0.4759 | |
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| 0.5322 | 2.7 | 5000 | 0.4818 | |
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| 0.5259 | 3.24 | 6000 | 0.4522 | |
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| 0.5259 | 3.78 | 7000 | 0.4632 | |
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| 0.5167 | 4.32 | 8000 | 0.4628 | |
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| 0.5167 | 4.86 | 9000 | 0.4345 | |
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| 0.5076 | 5.4 | 10000 | 0.4563 | |
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| 0.5076 | 5.94 | 11000 | 0.4326 | |
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| 0.494 | 6.48 | 12000 | 0.4424 | |
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| 0.4906 | 7.02 | 13000 | 0.4272 | |
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| 0.4906 | 7.56 | 14000 | 0.4164 | |
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| 0.4801 | 8.1 | 15000 | 0.4213 | |
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| 0.4801 | 8.64 | 16000 | 0.4320 | |
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| 0.4699 | 9.18 | 17000 | 0.4100 | |
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| 0.4699 | 9.72 | 18000 | 0.4127 | |
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| 0.4613 | 10.26 | 19000 | 0.4035 | |
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| 0.4613 | 10.8 | 20000 | 0.4039 | |
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| 0.4556 | 11.34 | 21000 | 0.4149 | |
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| 0.4556 | 11.88 | 22000 | 0.4092 | |
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| 0.4475 | 12.42 | 23000 | 0.3965 | |
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| 0.4475 | 12.96 | 24000 | 0.3973 | |
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| 0.4389 | 13.5 | 25000 | 0.4013 | |
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| 0.4349 | 14.04 | 26000 | 0.3797 | |
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| 0.4349 | 14.58 | 27000 | 0.3728 | |
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| 0.4288 | 15.12 | 28000 | 0.3834 | |
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| 0.4288 | 15.66 | 29000 | 0.3885 | |
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| 0.4222 | 16.2 | 30000 | 0.3820 | |
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| 0.4222 | 16.74 | 31000 | 0.3755 | |
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| 0.4152 | 17.28 | 32000 | 0.3693 | |
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| 0.4152 | 17.82 | 33000 | 0.3679 | |
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| 0.4122 | 18.36 | 34000 | 0.3605 | |
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| 0.4122 | 18.9 | 35000 | 0.3625 | |
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| 0.4077 | 19.44 | 36000 | 0.3631 | |
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| 0.4077 | 19.98 | 37000 | 0.3607 | |
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| 0.4 | 20.52 | 38000 | 0.3615 | |
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| 0.3972 | 21.06 | 39000 | 0.3561 | |
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| 0.3972 | 21.6 | 40000 | 0.3594 | |
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| 0.3953 | 22.14 | 41000 | 0.3554 | |
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| 0.3953 | 22.68 | 42000 | 0.3515 | |
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| 0.3903 | 23.22 | 43000 | 0.3539 | |
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| 0.3903 | 23.76 | 44000 | 0.3500 | |
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| 0.3878 | 24.3 | 45000 | 0.3489 | |
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| 0.3878 | 24.84 | 46000 | 0.3494 | |
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### Framework versions |
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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 |
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