adding batch to parameters. updating readme

README.md

@@ -14,4 +14,18 @@ model-index:
           - name: Accuracy
             type: Accuracy
             value: 0.9826
----
+---
+
+# Anyskin Slip Detection
+
+This model is designed for slip detection, trained on the [Anyskin Slip Detection Dataset](https://huggingface.co/datasets/pollen-robotics/anyskin_slip_detection). Its goal is to replicate the results presented in the [Anyskin paper](https://any-skin.github.io).
+
+## Training Code
+
+For the training code, please refer to this [repository](https://github.com/pollen-robotics/anyskin-slip-detection).
+
+## Citation
+
+  ```bibtex
+  Bhirangi, Raunaq, et al. "Anyskin: Plug-and-play skin sensing for robotic touch." arXiv preprint arXiv:2409.08276 (2024).
+  ```

params.json

@@ -1 +1 @@
-{"scaler": {"mean": [8.026537967645817, 11.66042378959173, 10.656610217811483, 7.613184994093653, -16.544877546269195, 6.79123375869554, -33.44293120484227, 16.401421743552557, -14.34237684619315, -19.622555672556036, -15.781563803851148, -8.233092624284618, 3.9396270168277057, 9.105127568888287, -0.4153522414080584], "scale": [73.88709297015735, 96.38865031045452, 58.39954271615279, 109.4303693913845, 125.09835152790978, 96.694631119986, 164.41310325140643, 96.69527973019925, 113.03062727534926, 59.19511911508219, 132.10151394889877, 49.58997734893265, 64.422807263786, 129.5964491219864, 65.32107466183254]}, "model": {"input_size": 15, "hidden_size": 128, "lstm_hidden_size": 128, "output_size": 1, "nlayers": 1, "epochs": 100}}
+{"scaler": {"mean": [8.026537967645817, 11.66042378959173, 10.656610217811483, 7.613184994093653, -16.544877546269195, 6.79123375869554, -33.44293120484227, 16.401421743552557, -14.34237684619315, -19.622555672556036, -15.781563803851148, -8.233092624284618, 3.9396270168277057, 9.105127568888287, -0.4153522414080584], "scale": [73.88709297015735, 96.38865031045452, 58.39954271615279, 109.4303693913845, 125.09835152790978, 96.694631119986, 164.41310325140643, 96.69527973019925, 113.03062727534926, 59.19511911508219, 132.10151394889877, 49.58997734893265, 64.422807263786, 129.5964491219864, 65.32107466183254]}, "model": {"input_size": 15, "hidden_size": 128, "lstm_hidden_size": 128, "output_size": 1, "nlayers": 1, "epochs": 100, "batch_size": 32}}