Instructions to use NLTuan/act_bi_pick_stack_obs4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use NLTuan/act_bi_pick_stack_obs4 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +2 -2
- config.json +1 -1
- model.safetensors +1 -1
- train_config.json +4 -4
README.md
CHANGED
|
@@ -6,8 +6,8 @@ model_name: act
|
|
| 6 |
pipeline_tag: robotics
|
| 7 |
tags:
|
| 8 |
- lerobot
|
| 9 |
-
- robotics
|
| 10 |
- act
|
|
|
|
| 11 |
---
|
| 12 |
|
| 13 |
# Model Card for act
|
|
@@ -81,7 +81,7 @@ The policy consumes these observation features and produces these action feature
|
|
| 81 |
| Training steps | 20000 |
|
| 82 |
| Batch size | 32 |
|
| 83 |
| Optimizer | adamw |
|
| 84 |
-
| Learning rate |
|
| 85 |
| Seed | 1000 |
|
| 86 |
| LeRobot version | 0.5.2 |
|
| 87 |
|
|
|
|
| 6 |
pipeline_tag: robotics
|
| 7 |
tags:
|
| 8 |
- lerobot
|
|
|
|
| 9 |
- act
|
| 10 |
+
- robotics
|
| 11 |
---
|
| 12 |
|
| 13 |
# Model Card for act
|
|
|
|
| 81 |
| Training steps | 20000 |
|
| 82 |
| Batch size | 32 |
|
| 83 |
| Optimizer | adamw |
|
| 84 |
+
| Learning rate | 5e-05 |
|
| 85 |
| Seed | 1000 |
|
| 86 |
| LeRobot version | 0.5.2 |
|
| 87 |
|
config.json
CHANGED
|
@@ -66,7 +66,7 @@
|
|
| 66 |
"temporal_ensemble_coeff": null,
|
| 67 |
"dropout": 0.1,
|
| 68 |
"kl_weight": 10.0,
|
| 69 |
-
"optimizer_lr":
|
| 70 |
"optimizer_weight_decay": 0.0001,
|
| 71 |
"optimizer_lr_backbone": 1e-05
|
| 72 |
}
|
|
|
|
| 66 |
"temporal_ensemble_coeff": null,
|
| 67 |
"dropout": 0.1,
|
| 68 |
"kl_weight": 10.0,
|
| 69 |
+
"optimizer_lr": 5e-05,
|
| 70 |
"optimizer_weight_decay": 0.0001,
|
| 71 |
"optimizer_lr_backbone": 1e-05
|
| 72 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 206763360
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0fd0d9baecd97826e24c16010c38f6b0809452032a9315bd4ca01b240c254c6a
|
| 3 |
size 206763360
|
train_config.json
CHANGED
|
@@ -150,13 +150,13 @@
|
|
| 150 |
"temporal_ensemble_coeff": null,
|
| 151 |
"dropout": 0.1,
|
| 152 |
"kl_weight": 10.0,
|
| 153 |
-
"optimizer_lr":
|
| 154 |
"optimizer_weight_decay": 0.0001,
|
| 155 |
"optimizer_lr_backbone": 1e-05
|
| 156 |
},
|
| 157 |
"reward_model": null,
|
| 158 |
"output_dir": "/kaggle/working/outputs/train/act_bi_pick_stack_obs4",
|
| 159 |
-
"job_name": "
|
| 160 |
"resume": false,
|
| 161 |
"seed": 1000,
|
| 162 |
"cudnn_deterministic": false,
|
|
@@ -175,7 +175,7 @@
|
|
| 175 |
"use_policy_training_preset": true,
|
| 176 |
"optimizer": {
|
| 177 |
"type": "adamw",
|
| 178 |
-
"lr":
|
| 179 |
"weight_decay": 0.0001,
|
| 180 |
"grad_clip_norm": 10.0,
|
| 181 |
"betas": [
|
|
@@ -199,7 +199,7 @@
|
|
| 199 |
"project": "act_bi_pick_stack",
|
| 200 |
"entity": null,
|
| 201 |
"notes": null,
|
| 202 |
-
"run_id": "
|
| 203 |
"mode": null,
|
| 204 |
"add_tags": true
|
| 205 |
},
|
|
|
|
| 150 |
"temporal_ensemble_coeff": null,
|
| 151 |
"dropout": 0.1,
|
| 152 |
"kl_weight": 10.0,
|
| 153 |
+
"optimizer_lr": 5e-05,
|
| 154 |
"optimizer_weight_decay": 0.0001,
|
| 155 |
"optimizer_lr_backbone": 1e-05
|
| 156 |
},
|
| 157 |
"reward_model": null,
|
| 158 |
"output_dir": "/kaggle/working/outputs/train/act_bi_pick_stack_obs4",
|
| 159 |
+
"job_name": "act_bi_pick_stack_obs4",
|
| 160 |
"resume": false,
|
| 161 |
"seed": 1000,
|
| 162 |
"cudnn_deterministic": false,
|
|
|
|
| 175 |
"use_policy_training_preset": true,
|
| 176 |
"optimizer": {
|
| 177 |
"type": "adamw",
|
| 178 |
+
"lr": 5e-05,
|
| 179 |
"weight_decay": 0.0001,
|
| 180 |
"grad_clip_norm": 10.0,
|
| 181 |
"betas": [
|
|
|
|
| 199 |
"project": "act_bi_pick_stack",
|
| 200 |
"entity": null,
|
| 201 |
"notes": null,
|
| 202 |
+
"run_id": "d4dh6hjm",
|
| 203 |
"mode": null,
|
| 204 |
"add_tags": true
|
| 205 |
},
|