Update README.md

README.md

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-license: artistic-2.0
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+**About**
+
+In table detection, we initialize the weights with a pre-trained CDeCNet model using COCO dataset. We re-train the model for five epochs using a stochastic gradient descent optimizer with a learning rate of 0.00125, the momentum of 0.9, and weight decay of 0.0001.
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+***Hardware Used***
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+We perform all the experiments on NVIDIA GeForce RTX 2080 Ti GPU with 12 GB GPU memory, Intel(R) Xeon(R) CPU E5-2640 v2 @ 2.00GHz, and 128 GB of RAM.
+
+**Table Detection Model & Training Parameter**
+***Optimizer*** 
+| Parameter |Value  |
+|--|--|
+| Type | SGD |
+| Learning Rate |0.00125  |
+| Momentum | 0.8 |
+| Weight Decay |0.001  |
+
+
+*** Learning Policy ***
+| Parameter |Value  |
+|--|--|
+| Policy | Step |
+|Warmup | Linear  |
+| Warmup Iteration | 100 |
+| Warmup Ratio |0.001  |
+| Step  | 4,16,32  |
+
+***General Parameter***
+| Parameter |Value  |
+|--|--|
+| Epoch | 5 |
+| Step Interval |50  |
+