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ChingizA
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detr

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detr
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End of training

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  1. README.md +26 -26
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.8513
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  ## Model description
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@@ -47,31 +47,31 @@ 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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- | 2.235 | 0.08 | 200 | 2.0882 |
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- | 2.0278 | 0.16 | 400 | 2.0542 |
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- | 1.7003 | 0.24 | 600 | 1.6411 |
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- | 1.7188 | 0.32 | 800 | 1.6111 |
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- | 1.4488 | 0.4 | 1000 | 1.3552 |
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- | 1.4492 | 0.48 | 1200 | 1.4768 |
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- | 1.3457 | 0.56 | 1400 | 1.3206 |
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- | 1.3914 | 0.64 | 1600 | 1.3176 |
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- | 1.2392 | 0.72 | 1800 | 1.1918 |
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- | 1.1335 | 0.8 | 2000 | 1.1535 |
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- | 1.1321 | 0.88 | 2200 | 1.1134 |
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- | 1.1088 | 0.96 | 2400 | 1.0808 |
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- | 1.0792 | 1.04 | 2600 | 1.0290 |
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- | 1.0801 | 1.12 | 2800 | 1.0240 |
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- | 0.9925 | 1.2 | 3000 | 0.9858 |
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- | 1.001 | 1.28 | 3200 | 0.9476 |
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- | 0.9654 | 1.36 | 3400 | 0.9389 |
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- | 0.9802 | 1.44 | 3600 | 0.9158 |
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- | 0.947 | 1.52 | 3800 | 0.9130 |
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- | 0.9489 | 1.6 | 4000 | 0.9004 |
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- | 0.8446 | 1.68 | 4200 | 0.8881 |
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- | 0.8854 | 1.76 | 4400 | 0.8774 |
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- | 0.9502 | 1.84 | 4600 | 0.8606 |
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- | 0.8816 | 1.92 | 4800 | 0.8616 |
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- | 0.8936 | 2.0 | 5000 | 0.8513 |
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  ### Framework versions
 
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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: 0.7342
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.1153 | 0.08 | 200 | 1.0413 |
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+ | 1.0375 | 0.16 | 400 | 0.9910 |
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+ | 1.0557 | 0.24 | 600 | 0.9525 |
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+ | 0.9463 | 0.32 | 800 | 0.9226 |
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+ | 0.9683 | 0.4 | 1000 | 0.9185 |
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+ | 0.9448 | 0.48 | 1200 | 0.8853 |
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+ | 0.9343 | 0.56 | 1400 | 0.9085 |
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+ | 0.9047 | 0.64 | 1600 | 0.8637 |
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+ | 0.9429 | 0.72 | 1800 | 0.8998 |
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+ | 0.846 | 0.8 | 2000 | 0.8494 |
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+ | 0.9111 | 0.88 | 2200 | 0.8380 |
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+ | 0.8987 | 0.96 | 2400 | 0.8217 |
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+ | 0.8348 | 1.04 | 2600 | 0.7994 |
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+ | 0.8578 | 1.12 | 2800 | 0.8096 |
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+ | 0.8063 | 1.2 | 3000 | 0.7920 |
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+ | 0.7922 | 1.28 | 3200 | 0.7797 |
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+ | 0.805 | 1.36 | 3400 | 0.7697 |
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+ | 0.8121 | 1.44 | 3600 | 0.7722 |
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+ | 0.798 | 1.52 | 3800 | 0.7664 |
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+ | 0.79 | 1.6 | 4000 | 0.7601 |
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+ | 0.7406 | 1.68 | 4200 | 0.7507 |
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+ | 0.7323 | 1.76 | 4400 | 0.7330 |
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+ | 0.8103 | 1.84 | 4600 | 0.7295 |
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+ | 0.7509 | 1.92 | 4800 | 0.7334 |
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+ | 0.7615 | 2.0 | 5000 | 0.7342 |
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  ### Framework versions