Upload policy weights, train config and readme

README.md

@@ -0,0 +1,62 @@
+---
+datasets: mhered/recording-test
+library_name: lerobot
+license: apache-2.0
+model_name: act
+pipeline_tag: robotics
+tags:
+- act
+- robotics
+- lerobot
+---
+
+# Model Card for act
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.
+
+
+This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
+See the full documentation at [LeRobot Docs](https://huggingface.co/docs/lerobot/index).
+
+---
+
+## How to Get Started with the Model
+
+For a complete walkthrough, see the [training guide](https://huggingface.co/docs/lerobot/il_robots#train-a-policy).
+Below is the short version on how to train and run inference/eval:
+
+### Train from scratch
+
+```bash
+lerobot-train \
+  --dataset.repo_id=${HF_USER}/<dataset> \
+  --policy.type=act \
+  --output_dir=outputs/train/<desired_policy_repo_id> \
+  --job_name=lerobot_training \
+  --policy.device=cuda \
+  --policy.repo_id=${HF_USER}/<desired_policy_repo_id>
+  --wandb.enable=true
+```
+
+_Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
+
+### Evaluate the policy/run inference
+
+```bash
+lerobot-record \
+  --robot.type=so100_follower \
+  --dataset.repo_id=<hf_user>/eval_<dataset> \
+  --policy.path=<hf_user>/<desired_policy_repo_id> \
+  --episodes=10
+```
+
+Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint.
+
+---
+
+## Model Details
+
+- **License:** apache-2.0

config.json

@@ -35,12 +35,12 @@
     },
     "device": "cuda",
     "use_amp": true,
-    "push_to_hub": false,
+    "push_to_hub": true,
     "repo_id": "mhered/my_act",
     "private": null,
     "tags": null,
     "license": null,
-    "pretrained_path": "mhered/my_act",
+    "pretrained_path": "outputs/train/act_so100_pato_test1/checkpoints/last/pretrained_model",
     "chunk_size": 100,
     "n_action_steps": 100,
     "normalization_mapping": {
@@ -50,7 +50,7 @@
     },
     "vision_backbone": "resnet18",
     "pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
-    "replace_final_stride_with_dilation": false,
+    "replace_final_stride_with_dilation": 0,
     "pre_norm": false,
     "dim_model": 512,
     "n_heads": 8,

model.safetensors

@@ -1,3 +1,3 @@
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-oid sha256:610d980958642fc20df1a604b880fe5f0f831c06668ba5028b6c8b9dd20b2917
+oid sha256:63e7a7d3ea2670cca9899858d7e9a2275d06633c0604082efee8cd1d9d984124
 size 206699736

train_config.json

@@ -103,12 +103,12 @@
         },
         "device": "cuda",
         "use_amp": true,
-        "push_to_hub": false,
+        "push_to_hub": true,
         "repo_id": "mhered/my_act",
         "private": null,
         "tags": null,
         "license": null,
-        "pretrained_path": "mhered/my_act",
+        "pretrained_path": "outputs/train/act_so100_pato_test1/checkpoints/last/pretrained_model",
         "chunk_size": 100,
         "n_action_steps": 100,
         "normalization_mapping": {
@@ -118,7 +118,7 @@
         },
         "vision_backbone": "resnet18",
         "pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
-        "replace_final_stride_with_dilation": false,
+        "replace_final_stride_with_dilation": 0,
         "pre_norm": false,
         "dim_model": 512,
         "n_heads": 8,
@@ -138,15 +138,15 @@
     },
     "output_dir": "outputs/train/act_so100_pato_test1",
     "job_name": "act_so100_pato_test",
-    "resume": false,
+    "resume": true,
     "seed": 1000,
     "num_workers": 2,
     "batch_size": 8,
-    "steps": 4000,
-    "eval_freq": 2000,
+    "steps": 20000,
+    "eval_freq": 5000,
     "log_freq": 200,
     "save_checkpoint": true,
-    "save_freq": 2000,
+    "save_freq": 5000,
     "use_policy_training_preset": true,
     "optimizer": {
         "type": "adamw",