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@@ -12,9 +12,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # detr-resnet-50_finetuned_bbatch
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- This model is a fine-tuned version of [AlreadyExists/detr-resnet-50_finetuned_bbatch](https://huggingface.co/AlreadyExists/detr-resnet-50_finetuned_bbatch) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6508
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  ## Model description
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@@ -46,59 +46,59 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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- | 1.1643 | 4.17 | 50 | 2.4138 |
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- | 1.1684 | 8.33 | 100 | 2.4418 |
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- | 1.1564 | 12.5 | 150 | 2.3408 |
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- | 1.1355 | 16.67 | 200 | 2.3903 |
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- | 1.1388 | 20.83 | 250 | 2.3484 |
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- | 1.139 | 25.0 | 300 | 2.4016 |
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- | 1.1098 | 29.17 | 350 | 2.4911 |
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- | 1.0869 | 33.33 | 400 | 2.3021 |
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- | 1.0871 | 37.5 | 450 | 2.4474 |
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- | 1.0793 | 41.67 | 500 | 2.4549 |
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- | 1.0691 | 45.83 | 550 | 2.5207 |
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- | 1.0539 | 50.0 | 600 | 2.4158 |
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- | 1.0579 | 54.17 | 650 | 2.4542 |
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- | 1.0365 | 58.33 | 700 | 2.4569 |
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- | 1.0221 | 62.5 | 750 | 2.5253 |
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- | 1.0173 | 66.67 | 800 | 2.4495 |
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- | 1.0241 | 70.83 | 850 | 2.4273 |
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- | 1.0111 | 75.0 | 900 | 2.4554 |
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- | 1.0127 | 79.17 | 950 | 2.4211 |
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- | 0.998 | 83.33 | 1000 | 2.5111 |
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- | 0.9869 | 87.5 | 1050 | 2.4077 |
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- | 0.9783 | 91.67 | 1100 | 2.5871 |
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- | 0.9802 | 95.83 | 1150 | 2.5365 |
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- | 0.983 | 100.0 | 1200 | 2.5527 |
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- | 0.9719 | 104.17 | 1250 | 2.5728 |
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- | 0.9578 | 108.33 | 1300 | 2.5637 |
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- | 0.9459 | 112.5 | 1350 | 2.5525 |
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- | 0.9353 | 116.67 | 1400 | 2.5476 |
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- | 0.94 | 120.83 | 1450 | 2.5374 |
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- | 0.9313 | 125.0 | 1500 | 2.6336 |
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- | 0.9236 | 129.17 | 1550 | 2.5556 |
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- | 0.9129 | 133.33 | 1600 | 2.5768 |
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- | 0.9231 | 137.5 | 1650 | 2.5904 |
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- | 0.9093 | 141.67 | 1700 | 2.6503 |
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- | 0.9169 | 145.83 | 1750 | 2.6057 |
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- | 0.9082 | 150.0 | 1800 | 2.6561 |
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- | 0.911 | 154.17 | 1850 | 2.6234 |
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- | 0.9019 | 158.33 | 1900 | 2.6442 |
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- | 0.8892 | 162.5 | 1950 | 2.6090 |
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- | 0.8891 | 166.67 | 2000 | 2.5849 |
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- | 0.8898 | 170.83 | 2050 | 2.6186 |
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- | 0.8745 | 175.0 | 2100 | 2.7664 |
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- | 0.8714 | 179.17 | 2150 | 2.6261 |
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- | 0.8902 | 183.33 | 2200 | 2.6510 |
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- | 0.8781 | 187.5 | 2250 | 2.7035 |
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- | 0.8826 | 191.67 | 2300 | 2.5627 |
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- | 0.8733 | 195.83 | 2350 | 2.5455 |
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- | 0.8694 | 200.0 | 2400 | 2.6508 |
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  ### Framework versions
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- - Transformers 4.27.4
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  - Pytorch 2.0.0+cu118
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  - Datasets 2.11.0
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  - Tokenizers 0.13.3
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  # detr-resnet-50_finetuned_bbatch
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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: 2.3729
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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+ | 4.0202 | 4.17 | 50 | 3.2912 |
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+ | 3.2043 | 8.33 | 100 | 3.1033 |
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+ | 3.0326 | 12.5 | 150 | 3.0882 |
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+ | 2.957 | 16.67 | 200 | 2.9938 |
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+ | 2.8396 | 20.83 | 250 | 2.8404 |
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+ | 2.7485 | 25.0 | 300 | 2.8785 |
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+ | 2.6515 | 29.17 | 350 | 2.7908 |
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+ | 2.5651 | 33.33 | 400 | 2.7162 |
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+ | 2.5172 | 37.5 | 450 | 2.6793 |
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+ | 2.434 | 41.67 | 500 | 2.6200 |
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+ | 2.3921 | 45.83 | 550 | 2.6078 |
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+ | 2.37 | 50.0 | 600 | 2.5634 |
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+ | 2.3211 | 54.17 | 650 | 2.5730 |
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+ | 2.2658 | 58.33 | 700 | 2.4883 |
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+ | 2.2487 | 62.5 | 750 | 2.6039 |
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+ | 2.2001 | 66.67 | 800 | 2.4645 |
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+ | 2.1767 | 70.83 | 850 | 2.5015 |
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+ | 2.1533 | 75.0 | 900 | 2.4727 |
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+ | 2.1489 | 79.17 | 950 | 2.4663 |
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+ | 2.1181 | 83.33 | 1000 | 2.4865 |
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+ | 2.0739 | 87.5 | 1050 | 2.4522 |
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+ | 2.0664 | 91.67 | 1100 | 2.4344 |
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+ | 2.0347 | 95.83 | 1150 | 2.4347 |
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+ | 2.0175 | 100.0 | 1200 | 2.4883 |
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+ | 1.9989 | 104.17 | 1250 | 2.4523 |
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+ | 1.9773 | 108.33 | 1300 | 2.4971 |
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+ | 1.9473 | 112.5 | 1350 | 2.5026 |
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+ | 1.9431 | 116.67 | 1400 | 2.4029 |
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+ | 1.9274 | 120.83 | 1450 | 2.4887 |
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+ | 1.907 | 125.0 | 1500 | 2.4216 |
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+ | 1.9006 | 129.17 | 1550 | 2.4143 |
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+ | 1.8775 | 133.33 | 1600 | 2.4107 |
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+ | 1.8795 | 137.5 | 1650 | 2.3722 |
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+ | 1.8582 | 141.67 | 1700 | 2.3952 |
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+ | 1.8538 | 145.83 | 1750 | 2.3964 |
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+ | 1.8409 | 150.0 | 1800 | 2.4083 |
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+ | 1.8302 | 154.17 | 1850 | 2.4013 |
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+ | 1.8203 | 158.33 | 1900 | 2.3768 |
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+ | 1.8112 | 162.5 | 1950 | 2.4538 |
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+ | 1.7935 | 166.67 | 2000 | 2.3903 |
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+ | 1.8035 | 170.83 | 2050 | 2.3707 |
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+ | 1.7955 | 175.0 | 2100 | 2.3588 |
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+ | 1.7786 | 179.17 | 2150 | 2.3775 |
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+ | 1.7988 | 183.33 | 2200 | 2.3376 |
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+ | 1.7808 | 187.5 | 2250 | 2.3629 |
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+ | 1.7802 | 191.67 | 2300 | 2.4191 |
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+ | 1.769 | 195.83 | 2350 | 2.3897 |
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+ | 1.7677 | 200.0 | 2400 | 2.3729 |
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  ### Framework versions
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+ - Transformers 4.28.1
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  - Pytorch 2.0.0+cu118
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  - Datasets 2.11.0
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  - Tokenizers 0.13.3