Hugging Face's logo

JayLee131
/
vqbet_pusht2

Robotics
Transformers
Safetensors
Inference Endpoints
Model card Files Community
vqbet_pusht2
File size: 3,170 Bytes 
115b29c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
30dd984
115b29c
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
 
resume: false
device: cuda
use_amp: false
seed: 100000
dataset_repo_id: lerobot/pusht
video_backend: pyav
training:
  offline_steps: 250000
  online_steps: 0
  online_steps_between_rollouts: 1
  online_sampling_ratio: 0.5
  online_env_seed: ???
  eval_freq: 20000
  log_freq: 250
  save_checkpoint: true
  save_freq: 20000
  num_workers: 4
  batch_size: 64
  image_transforms:
    enable: false
    max_num_transforms: 3
    random_order: false
    brightness:
      weight: 1
      min_max:
      - 0.8
      - 1.2
    contrast:
      weight: 1
      min_max:
      - 0.8
      - 1.2
    saturation:
      weight: 1
      min_max:
      - 0.5
      - 1.5
    hue:
      weight: 1
      min_max:
      - -0.05
      - 0.05
    sharpness:
      weight: 1
      min_max:
      - 0.8
      - 1.2
  grad_clip_norm: 10
  lr: 0.0001
  lr_scheduler: cosine
  lr_warmup_steps: 500
  adam_betas:
  - 0.95
  - 0.999
  adam_eps: 1.0e-08
  adam_weight_decay: 1.0e-06
  vqvae_lr: 0.001
  n_vqvae_training_steps: 20000
  bet_weight_decay: 0.0002
  bet_learning_rate: 5.5e-05
  bet_betas:
  - 0.9
  - 0.999
  delta_timestamps:
    observation.image:
    - -0.4
    - -0.3
    - -0.2
    - -0.1
    - 0.0
    observation.state:
    - -0.4
    - -0.3
    - -0.2
    - -0.1
    - 0.0
    action:
    - -0.4
    - -0.3
    - -0.2
    - -0.1
    - 0.0
    - 0.1
    - 0.2
    - 0.3
    - 0.4
    - 0.5
    - 0.6
    - 0.7
    - 0.8
    - 0.9
    - 1.0
eval:
  n_episodes: 500
  batch_size: 50
  use_async_envs: false
wandb:
  enable: true
  disable_artifact: false
  project: lerobot
  notes: ''
fps: 10
env:
  name: pusht
  task: PushT-v0
  image_size: 96
  state_dim: 2
  action_dim: 2
  fps: ${fps}
  episode_length: 300
  gym:
    obs_type: pixels_agent_pos
    render_mode: rgb_array
    visualization_width: 384
    visualization_height: 384
override_dataset_stats:
  observation.image:
    mean:
    - - - 0.5
    - - - 0.5
    - - - 0.5
    std:
    - - - 0.5
    - - - 0.5
    - - - 0.5
  observation.state:
    min:
    - 13.456424
    - 32.938293
    max:
    - 496.14618
    - 510.9579
  action:
    min:
    - 12.0
    - 25.0
    max:
    - 511.0
    - 511.0
policy:
  name: vqbet
  n_obs_steps: 5
  n_action_pred_token: 7
  action_chunk_size: 5
  input_shapes:
    observation.image:
    - 3
    - 96
    - 96
    observation.state:
    - ${env.state_dim}
  output_shapes:
    action:
    - ${env.action_dim}
  input_normalization_modes:
    observation.image: mean_std
    observation.state: min_max
  output_normalization_modes:
    action: min_max
  vision_backbone: resnet18
  crop_shape:
  - 84
  - 84
  crop_is_random: true
  pretrained_backbone_weights: null
  use_group_norm: true
  spatial_softmax_num_keypoints: 32
  n_vqvae_training_steps: ${training.n_vqvae_training_steps}
  vqvae_n_embed: 16
  vqvae_embedding_dim: 256
  vqvae_enc_hidden_dim: 128
  gpt_block_size: 500
  gpt_input_dim: 512
  gpt_output_dim: 512
  gpt_n_layer: 8
  gpt_n_head: 8
  gpt_hidden_dim: 512
  dropout: 0.1
  mlp_hidden_dim: 1024
  offset_loss_weight: 10000.0
  primary_code_loss_weight: 5.0
  secondary_code_loss_weight: 0.5
  bet_softmax_temperature: 0.01
  sequentially_select: false