aliberts HF staff commited on
Commit
a25d928
·
verified ·
1 Parent(s): 24a053c

remove_hydra (#2)

Browse files

- Upload folder using huggingface_hub (b06c88b1bf33993b7f25b2cd64dba79923eda85b)
- Upload eval_info.json with huggingface_hub (ba8a9926fc085c3785f144e2b676bc35ca053a5c)
- Delete config.yaml (81e6614b6692f4552ff46beea8dc97d1ba4e9314)
- Update README (21573fe81522899ec7144da09e14c34034c13e6d)
- Use 175k steps checkpoint (d3d143b0342488252497853815b27ce3c0384c6b)
- Cleanup, update training curves (6d8bb7de11d55b2100c12ca4b73a6a72e2754369)
- Update results (f322b4fdce74e7d3c4e0636fb1135814996eabf2)

README.md CHANGED
@@ -2,6 +2,11 @@
2
  license: apache-2.0
3
  datasets:
4
  - lerobot/pusht
 
 
 
 
 
5
  pipeline_tag: robotics
6
  ---
7
  # Model Card for Diffusion Policy / PushT
@@ -15,31 +20,27 @@ See the [LeRobot library](https://github.com/huggingface/lerobot) (particularly
15
 
16
  ## Training Details
17
 
18
- The model was trained using [LeRobot's training script](https://github.com/huggingface/lerobot/blob/d747195c5733c4f68d4bfbe62632d6fc1b605712/lerobot/scripts/train.py) and with the [pusht](https://huggingface.co/datasets/lerobot/pusht/tree/v1.3) dataset, using this command:
 
 
19
 
20
  ```bash
21
  python lerobot/scripts/train.py \
22
- hydra.run.dir=outputs/train/diffusion_pusht \
23
- hydra.job.name=diffusion_pusht \
24
- policy=diffusion training.save_model=true \
25
- env=pusht \
26
- env.task=PushT-v0 \
27
- dataset_repo_id=lerobot/pusht \
28
- training.offline_steps=200000 \
29
- training.save_freq=20000 \
30
- training.eval_freq=10000 \
31
- eval.n_episodes=50 \
32
- wandb.enable=true \
33
- wandb.disable_artifact=true \
34
- device=cuda
35
  ```
36
 
37
 
38
- The training curves may be found at https://wandb.ai/alexander-soare/Alexander-LeRobot/runs/508luayd.
39
-
40
- This took about 7 hours to train on an Nvida RTX 3090.
41
-
42
- _Note: At the time of training, [this PR](https://github.com/huggingface/lerobot/pull/129) was also incorporated._
43
 
44
  ## Evaluation
45
 
@@ -48,12 +49,22 @@ The model was evaluated on the `PushT` environment from [gym-pusht](https://gith
48
  - Maximum overlap with target (seen as `eval/avg_max_reward` in the charts above). This ranges in [0, 1].
49
  - Success: whether or not the maximum overlap is at least 95%.
50
 
51
- Here are the metrics for 500 episodes worth of evaluation. For the succes rate we add an extra row with confidence bounds. This assumes a uniform prior over success probability and computes the beta posterior, then calculates the mean and lower/upper confidence bounds (with a 68.2% confidence interval centered on the mean). The "Theirs" column is for an equivalent model trained on the original Diffusion Policy repository and evaluated on LeRobot (the model weights may be found in the [`original_dp_repo`](https://huggingface.co/lerobot/diffusion_pusht/tree/original_dp_repo) branch of this respository).
52
 
53
  <blank>|Ours|Theirs
54
  -|-|-
55
- Average max. overlap ratio | 0.959 | 0.957
56
- Success rate for 500 episodes (%) | 63.8 | 64.2
57
- Beta distribution lower/mean/upper (%) | 61.6 / 63.7 / 65.9 | 62.0 / 64.1 / 66.3
58
 
59
- The results of each of the individual rollouts may be found in [eval_info.json](eval_info.json).
 
 
 
 
 
 
 
 
 
 
 
 
2
  license: apache-2.0
3
  datasets:
4
  - lerobot/pusht
5
+ tags:
6
+ - diffusion-policy
7
+ - model_hub_mixin
8
+ - pytorch_model_hub_mixin
9
+ - robotics
10
  pipeline_tag: robotics
11
  ---
12
  # Model Card for Diffusion Policy / PushT
 
20
 
21
  ## Training Details
22
 
23
+ Trained with [LeRobot@3c0a209](https://github.com/huggingface/lerobot/tree/3c0a209f9fac4d2a57617e686a7f2a2309144ba2).
24
+
25
+ The model was trained using [LeRobot's training script](https://github.com/huggingface/lerobot/blob/main/lerobot/scripts/train.py) and with the [pusht](https://huggingface.co/datasets/lerobot/pusht) dataset, using this command:
26
 
27
  ```bash
28
  python lerobot/scripts/train.py \
29
+ --output_dir=outputs/train/diffusion_pusht \
30
+ --policy.type=diffusion \
31
+ --dataset.repo_id=lerobot/pusht \
32
+ --seed=100000 \
33
+ --env.type=pusht \
34
+ --batch_size=64 \
35
+ --offline.steps=200000 \
36
+ --eval_freq=25000 \
37
+ --save_freq=25000 \
38
+ --wandb.enable=true
 
 
 
39
  ```
40
 
41
 
42
+ The training curves may be found at https://wandb.ai/aliberts/lerobot/runs/s7elvf4r.
43
+ The current model corresponds to the checkpoint at 175k steps.
 
 
 
44
 
45
  ## Evaluation
46
 
 
49
  - Maximum overlap with target (seen as `eval/avg_max_reward` in the charts above). This ranges in [0, 1].
50
  - Success: whether or not the maximum overlap is at least 95%.
51
 
52
+ Here are the metrics for 500 episodes worth of evaluation. The "Theirs" column is for an equivalent model trained on the original Diffusion Policy repository and evaluated on LeRobot (the model weights may be found in the [`original_dp_repo`](https://huggingface.co/lerobot/diffusion_pusht/tree/original_dp_repo) branch of this respository).
53
 
54
  <blank>|Ours|Theirs
55
  -|-|-
56
+ Average max. overlap ratio | 0.955 | 0.957
57
+ Success rate for 500 episodes (%) | 65.4 | 64.2
 
58
 
59
+ The results of each of the individual rollouts may be found in [eval_info.json](eval_info.json).
60
+ It was produced after training with this command:
61
+ ```bash
62
+ python lerobot/scripts/eval.py \
63
+ --policy.path=outputs/train/diffusion_pusht/checkpoints/175000/pretrained_model \
64
+ --output_dir=outputs/eval/diffusion_pusht/175000 \
65
+ --env.type=pusht \
66
+ --eval.n_episodes=500 \
67
+ --eval.batch_size=50 \
68
+ --device=cuda \
69
+ --use_amp=false
70
+ ```
config.json CHANGED
@@ -1,53 +1,74 @@
1
  {
2
- "n_obs_steps": 2,
3
- "horizon": 16,
4
- "n_action_steps": 8,
5
- "input_shapes": {
6
- "observation.image": [
7
- 3,
8
- 96,
9
- 96
10
- ],
11
- "observation.state": [
12
- 2
13
- ]
14
- },
15
- "output_shapes": {
16
- "action": [
17
- 2
18
- ]
19
- },
20
- "input_normalization_modes": {
21
- "observation.image": "mean_std",
22
- "observation.state": "min_max"
23
- },
24
- "output_normalization_modes": {
25
- "action": "min_max"
26
- },
27
- "vision_backbone": "resnet18",
28
  "crop_shape": [
29
  84,
30
  84
31
  ],
32
- "crop_is_random": true,
33
- "pretrained_backbone_weights": null,
34
- "use_group_norm": true,
35
- "spatial_softmax_num_keypoints": 32,
36
  "down_dims": [
37
  512,
38
  1024,
39
  2048
40
  ],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
41
  "kernel_size": 5,
 
42
  "n_groups": 8,
43
- "diffusion_step_embed_dim": 128,
44
- "use_film_scale_modulation": true,
 
 
 
 
 
 
45
  "num_train_timesteps": 100,
46
- "beta_schedule": "squaredcos_cap_v2",
47
- "beta_start": 0.0001,
48
- "beta_end": 0.02,
 
 
 
 
 
 
 
 
 
 
 
 
49
  "prediction_type": "epsilon",
50
- "clip_sample": true,
51
- "clip_sample_range": 1.0,
52
- "num_inference_steps": 100
 
 
 
 
 
 
53
  }
 
1
  {
2
+ "beta_end": 0.02,
3
+ "beta_schedule": "squaredcos_cap_v2",
4
+ "beta_start": 0.0001,
5
+ "clip_sample": true,
6
+ "clip_sample_range": 1.0,
7
+ "crop_is_random": true,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8
  "crop_shape": [
9
  84,
10
  84
11
  ],
12
+ "diffusion_step_embed_dim": 128,
13
+ "do_mask_loss_for_padding": false,
 
 
14
  "down_dims": [
15
  512,
16
  1024,
17
  2048
18
  ],
19
+ "drop_n_last_frames": 7,
20
+ "horizon": 16,
21
+ "input_features": {
22
+ "observation.image": {
23
+ "shape": [
24
+ 3,
25
+ 96,
26
+ 96
27
+ ],
28
+ "type": "VISUAL"
29
+ },
30
+ "observation.state": {
31
+ "shape": [
32
+ 2
33
+ ],
34
+ "type": "STATE"
35
+ }
36
+ },
37
  "kernel_size": 5,
38
+ "n_action_steps": 8,
39
  "n_groups": 8,
40
+ "n_obs_steps": 2,
41
+ "noise_scheduler_type": "DDPM",
42
+ "normalization_mapping": {
43
+ "ACTION": "MIN_MAX",
44
+ "STATE": "MIN_MAX",
45
+ "VISUAL": "MEAN_STD"
46
+ },
47
+ "num_inference_steps": null,
48
  "num_train_timesteps": 100,
49
+ "optimizer_betas": [
50
+ 0.95,
51
+ 0.999
52
+ ],
53
+ "optimizer_eps": 1e-08,
54
+ "optimizer_lr": 0.0001,
55
+ "optimizer_weight_decay": 1e-06,
56
+ "output_features": {
57
+ "action": {
58
+ "shape": [
59
+ 2
60
+ ],
61
+ "type": "ACTION"
62
+ }
63
+ },
64
  "prediction_type": "epsilon",
65
+ "pretrained_backbone_weights": null,
66
+ "scheduler_name": "cosine",
67
+ "scheduler_warmup_steps": 500,
68
+ "spatial_softmax_num_keypoints": 32,
69
+ "type": "diffusion",
70
+ "use_film_scale_modulation": true,
71
+ "use_group_norm": true,
72
+ "use_separate_rgb_encoder_per_camera": false,
73
+ "vision_backbone": "resnet18"
74
  }
config.yaml DELETED
@@ -1,141 +0,0 @@
1
- device: cuda
2
- use_amp: false
3
- seed: 100000
4
- dataset_repo_id: lerobot/pusht
5
- training:
6
- offline_steps: 200000
7
- online_steps: 0
8
- online_steps_between_rollouts: 1
9
- online_sampling_ratio: 0.5
10
- online_env_seed: ???
11
- eval_freq: 10000
12
- save_freq: 20000
13
- log_freq: 250
14
- save_model: true
15
- batch_size: 64
16
- grad_clip_norm: 10
17
- lr: 0.0001
18
- lr_scheduler: cosine
19
- lr_warmup_steps: 500
20
- adam_betas:
21
- - 0.95
22
- - 0.999
23
- adam_eps: 1.0e-08
24
- adam_weight_decay: 1.0e-06
25
- delta_timestamps:
26
- observation.image:
27
- - -0.1
28
- - 0.0
29
- observation.state:
30
- - -0.1
31
- - 0.0
32
- action:
33
- - -0.1
34
- - 0.0
35
- - 0.1
36
- - 0.2
37
- - 0.3
38
- - 0.4
39
- - 0.5
40
- - 0.6
41
- - 0.7
42
- - 0.8
43
- - 0.9
44
- - 1.0
45
- - 1.1
46
- - 1.2
47
- - 1.3
48
- - 1.4
49
- n_end_keyframes_dropped: ${policy.horizon} - ${policy.n_action_steps} - ${policy.n_obs_steps}
50
- + 1
51
- eval:
52
- n_episodes: 50
53
- batch_size: 50
54
- use_async_envs: false
55
- wandb:
56
- enable: true
57
- disable_artifact: true
58
- project: lerobot
59
- notes: ''
60
- fps: 10
61
- env:
62
- name: pusht
63
- task: PushT-v0
64
- image_size: 96
65
- state_dim: 2
66
- action_dim: 2
67
- fps: ${fps}
68
- episode_length: 300
69
- gym:
70
- obs_type: pixels_agent_pos
71
- render_mode: rgb_array
72
- visualization_width: 384
73
- visualization_height: 384
74
- override_dataset_stats:
75
- observation.image:
76
- mean:
77
- - - - 0.5
78
- - - - 0.5
79
- - - - 0.5
80
- std:
81
- - - - 0.5
82
- - - - 0.5
83
- - - - 0.5
84
- observation.state:
85
- min:
86
- - 13.456424
87
- - 32.938293
88
- max:
89
- - 496.14618
90
- - 510.9579
91
- action:
92
- min:
93
- - 12.0
94
- - 25.0
95
- max:
96
- - 511.0
97
- - 511.0
98
- policy:
99
- name: diffusion
100
- n_obs_steps: 2
101
- horizon: 16
102
- n_action_steps: 8
103
- input_shapes:
104
- observation.image:
105
- - 3
106
- - 96
107
- - 96
108
- observation.state:
109
- - ${env.state_dim}
110
- output_shapes:
111
- action:
112
- - ${env.action_dim}
113
- input_normalization_modes:
114
- observation.image: mean_std
115
- observation.state: min_max
116
- output_normalization_modes:
117
- action: min_max
118
- vision_backbone: resnet18
119
- crop_shape:
120
- - 84
121
- - 84
122
- crop_is_random: true
123
- pretrained_backbone_weights: null
124
- use_group_norm: true
125
- spatial_softmax_num_keypoints: 32
126
- down_dims:
127
- - 512
128
- - 1024
129
- - 2048
130
- kernel_size: 5
131
- n_groups: 8
132
- diffusion_step_embed_dim: 128
133
- use_film_scale_modulation: true
134
- num_train_timesteps: 100
135
- beta_schedule: squaredcos_cap_v2
136
- beta_start: 0.0001
137
- beta_end: 0.02
138
- prediction_type: epsilon
139
- clip_sample: true
140
- clip_sample_range: 1.0
141
- num_inference_steps: 100
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
eval_avg_max_reward.csv DELETED
@@ -1,21 +0,0 @@
1
- Step,diffusion_pusht_final - eval/avg_max_reward
2
- 10000,0.727783498535056
3
- 20000,0.926793976568431
4
- 30000,0.928166216058858
5
- 40000,0.958328167172369
6
- 50000,0.943188394510958
7
- 60000,0.937613393970094
8
- 70000,0.964618642115711
9
- 80000,0.978192933234
10
- 90000,0.953355139113338
11
- 100000,0.950833988995675
12
- 110000,0.982668314916378
13
- 120000,0.939619379505442
14
- 130000,0.959122695767039
15
- 140000,0.968145088219487
16
- 150000,0.959675288643079
17
- 160000,0.988640977099844
18
- 170000,0.943671615378961
19
- 180000,0.965194043468211
20
- 190000,0.963914309028651
21
- 200000,0.959864101861565
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
eval_info.json CHANGED
The diff for this file is too large to render. See raw diff
 
eval_pc_success.csv DELETED
@@ -1,21 +0,0 @@
1
- Step,diffusion_pusht_final - eval/pc_success
2
- 10000,12
3
- 20000,58
4
- 30000,52
5
- 40000,66
6
- 50000,66
7
- 60000,66
8
- 70000,64
9
- 80000,70
10
- 90000,68
11
- 100000,68
12
- 110000,70
13
- 120000,58
14
- 130000,70
15
- 140000,74
16
- 150000,74
17
- 160000,64
18
- 170000,64
19
- 180000,70
20
- 190000,64
21
- 200000,62
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:877969d58d12af315d8c672a2328b3984071901b6f71bdf592b6f131056b520f
3
- size 1050862612
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:995d14d35db57d95c35ad9704c3d79c8612b7bc45f3877e5c46c2cdc516856a8
3
+ size 1050862408
train_config.json ADDED
@@ -0,0 +1,233 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "dataset": {
3
+ "repo_id": "lerobot/pusht",
4
+ "episodes": null,
5
+ "image_transforms": {
6
+ "enable": false,
7
+ "max_num_transforms": 3,
8
+ "random_order": false,
9
+ "tfs": {
10
+ "brightness": {
11
+ "weight": 1.0,
12
+ "type": "ColorJitter",
13
+ "kwargs": {
14
+ "brightness": [
15
+ 0.8,
16
+ 1.2
17
+ ]
18
+ }
19
+ },
20
+ "contrast": {
21
+ "weight": 1.0,
22
+ "type": "ColorJitter",
23
+ "kwargs": {
24
+ "contrast": [
25
+ 0.8,
26
+ 1.2
27
+ ]
28
+ }
29
+ },
30
+ "saturation": {
31
+ "weight": 1.0,
32
+ "type": "ColorJitter",
33
+ "kwargs": {
34
+ "saturation": [
35
+ 0.5,
36
+ 1.5
37
+ ]
38
+ }
39
+ },
40
+ "hue": {
41
+ "weight": 1.0,
42
+ "type": "ColorJitter",
43
+ "kwargs": {
44
+ "hue": [
45
+ -0.05,
46
+ 0.05
47
+ ]
48
+ }
49
+ },
50
+ "sharpness": {
51
+ "weight": 1.0,
52
+ "type": "SharpnessJitter",
53
+ "kwargs": {
54
+ "sharpness": [
55
+ 0.5,
56
+ 1.5
57
+ ]
58
+ }
59
+ }
60
+ }
61
+ },
62
+ "local_files_only": false,
63
+ "use_imagenet_stats": true,
64
+ "video_backend": "pyav"
65
+ },
66
+ "env": {
67
+ "type": "pusht",
68
+ "task": "PushT-v0",
69
+ "fps": 10,
70
+ "features": {
71
+ "action": {
72
+ "type": "ACTION",
73
+ "shape": [
74
+ 2
75
+ ]
76
+ },
77
+ "agent_pos": {
78
+ "type": "STATE",
79
+ "shape": [
80
+ 2
81
+ ]
82
+ },
83
+ "pixels": {
84
+ "type": "VISUAL",
85
+ "shape": [
86
+ 384,
87
+ 384,
88
+ 3
89
+ ]
90
+ }
91
+ },
92
+ "features_map": {
93
+ "action": "action",
94
+ "agent_pos": "observation.state",
95
+ "environment_state": "observation.environment_state",
96
+ "pixels": "observation.image"
97
+ },
98
+ "episode_length": 300,
99
+ "obs_type": "pixels_agent_pos",
100
+ "render_mode": "rgb_array",
101
+ "visualization_width": 384,
102
+ "visualization_height": 384
103
+ },
104
+ "policy": {
105
+ "type": "diffusion",
106
+ "n_obs_steps": 2,
107
+ "normalization_mapping": {
108
+ "VISUAL": "MEAN_STD",
109
+ "STATE": "MIN_MAX",
110
+ "ACTION": "MIN_MAX"
111
+ },
112
+ "input_features": {
113
+ "observation.image": {
114
+ "type": "VISUAL",
115
+ "shape": [
116
+ 3,
117
+ 96,
118
+ 96
119
+ ]
120
+ },
121
+ "observation.state": {
122
+ "type": "STATE",
123
+ "shape": [
124
+ 2
125
+ ]
126
+ }
127
+ },
128
+ "output_features": {
129
+ "action": {
130
+ "type": "ACTION",
131
+ "shape": [
132
+ 2
133
+ ]
134
+ }
135
+ },
136
+ "horizon": 16,
137
+ "n_action_steps": 8,
138
+ "drop_n_last_frames": 7,
139
+ "vision_backbone": "resnet18",
140
+ "crop_shape": [
141
+ 84,
142
+ 84
143
+ ],
144
+ "crop_is_random": true,
145
+ "pretrained_backbone_weights": null,
146
+ "use_group_norm": true,
147
+ "spatial_softmax_num_keypoints": 32,
148
+ "use_separate_rgb_encoder_per_camera": false,
149
+ "down_dims": [
150
+ 512,
151
+ 1024,
152
+ 2048
153
+ ],
154
+ "kernel_size": 5,
155
+ "n_groups": 8,
156
+ "diffusion_step_embed_dim": 128,
157
+ "use_film_scale_modulation": true,
158
+ "noise_scheduler_type": "DDPM",
159
+ "num_train_timesteps": 100,
160
+ "beta_schedule": "squaredcos_cap_v2",
161
+ "beta_start": 0.0001,
162
+ "beta_end": 0.02,
163
+ "prediction_type": "epsilon",
164
+ "clip_sample": true,
165
+ "clip_sample_range": 1.0,
166
+ "num_inference_steps": null,
167
+ "do_mask_loss_for_padding": false,
168
+ "optimizer_lr": 0.0001,
169
+ "optimizer_betas": [
170
+ 0.95,
171
+ 0.999
172
+ ],
173
+ "optimizer_eps": 1e-08,
174
+ "optimizer_weight_decay": 1e-06,
175
+ "scheduler_name": "cosine",
176
+ "scheduler_warmup_steps": 500
177
+ },
178
+ "output_dir": "outputs/train/2025-01-17/11-51-15_pusht_diffusion",
179
+ "job_name": "pusht_diffusion",
180
+ "resume": false,
181
+ "device": "cuda",
182
+ "use_amp": false,
183
+ "seed": 100000,
184
+ "num_workers": 4,
185
+ "batch_size": 64,
186
+ "eval_freq": 25000,
187
+ "log_freq": 200,
188
+ "save_checkpoint": true,
189
+ "save_freq": 25000,
190
+ "offline": {
191
+ "steps": 200000
192
+ },
193
+ "online": {
194
+ "steps": 0,
195
+ "rollout_n_episodes": 1,
196
+ "rollout_batch_size": 1,
197
+ "steps_between_rollouts": null,
198
+ "sampling_ratio": 0.5,
199
+ "env_seed": null,
200
+ "buffer_capacity": null,
201
+ "buffer_seed_size": 0,
202
+ "do_rollout_async": false
203
+ },
204
+ "use_policy_training_preset": true,
205
+ "optimizer": {
206
+ "type": "adam",
207
+ "lr": 0.0001,
208
+ "betas": [
209
+ 0.95,
210
+ 0.999
211
+ ],
212
+ "eps": 1e-08,
213
+ "weight_decay": 1e-06,
214
+ "grad_clip_norm": 10.0
215
+ },
216
+ "scheduler": {
217
+ "type": "diffuser",
218
+ "num_warmup_steps": 500,
219
+ "name": "cosine"
220
+ },
221
+ "eval": {
222
+ "n_episodes": 50,
223
+ "batch_size": 50,
224
+ "use_async_envs": false
225
+ },
226
+ "wandb": {
227
+ "enable": true,
228
+ "disable_artifact": false,
229
+ "project": "lerobot",
230
+ "entity": null,
231
+ "notes": null
232
+ }
233
+ }
train_loss.csv DELETED
@@ -1,801 +0,0 @@
1
- Step,diffusion_pusht_final - train/loss
2
- 0,1.14531636238098
3
- 250,0.073100820183754
4
- 500,0.0622915513813496
5
- 750,0.0509208142757416
6
- 1000,0.0519833080470562
7
- 1250,0.0714620426297188
8
- 1500,0.0595633871853352
9
- 1750,0.0701294019818306
10
- 2000,0.0404818207025528
11
- 2250,0.0368309617042541
12
- 2500,0.0336403548717499
13
- 2750,0.0423509329557419
14
- 3000,0.0454331822693348
15
- 3250,0.0351408272981644
16
- 3500,0.0273116938769817
17
- 3750,0.030073381960392
18
- 4000,0.041268415749073
19
- 4250,0.0356700122356415
20
- 4500,0.0379195064306259
21
- 4750,0.0442487448453903
22
- 5000,0.0364686772227287
23
- 5250,0.0413501709699631
24
- 5500,0.0466006025671959
25
- 5750,0.042169101536274
26
- 6000,0.0296320710331202
27
- 6250,0.0266561340540647
28
- 6500,0.0489253364503384
29
- 6750,0.0388820692896843
30
- 7000,0.0391516834497452
31
- 7250,0.0256843436509371
32
- 7500,0.0548840276896954
33
- 7750,0.0174913369119167
34
- 8000,0.0552169159054756
35
- 8250,0.0380522198975086
36
- 8500,0.0270846486091614
37
- 8750,0.0255028437823057
38
- 9000,0.0310249011963606
39
- 9250,0.0284159183502197
40
- 9500,0.051392674446106
41
- 9750,0.0374260172247887
42
- 10000,0.0327198877930641
43
- 10250,0.0372582376003265
44
- 10500,0.0411925092339516
45
- 10750,0.0287556014955044
46
- 11000,0.041535560041666
47
- 11250,0.0269710756838322
48
- 11500,0.0263594388961792
49
- 11750,0.0315541625022888
50
- 12000,0.0217097699642181
51
- 12250,0.0339197143912315
52
- 12500,0.0240575652569532
53
- 12750,0.0361779518425465
54
- 13000,0.0205294899642467
55
- 13250,0.0211157836019993
56
- 13500,0.0400474518537521
57
- 13750,0.022750973701477
58
- 14000,0.018504686653614
59
- 14250,0.0274174194782972
60
- 14500,0.0304331686347723
61
- 14750,0.039531484246254
62
- 15000,0.0468998104333878
63
- 15250,0.0336333326995373
64
- 15500,0.0333245918154716
65
- 15750,0.0248412992805243
66
- 16000,0.0269852876663208
67
- 16250,0.0360851474106312
68
- 16500,0.0192200150340796
69
- 16750,0.022846644744277
70
- 17000,0.03960882127285
71
- 17250,0.0239151921123266
72
- 17500,0.0194619800895453
73
- 17750,0.016773447394371
74
- 18000,0.0228232033550739
75
- 18250,0.0167265385389328
76
- 18500,0.0171782895922661
77
- 18750,0.0392149984836578
78
- 19000,0.0214392431080341
79
- 19250,0.0200660936534405
80
- 19500,0.0358948037028313
81
- 19750,0.03781783208251
82
- 20000,0.0377031713724136
83
- 20250,0.0184616446495056
84
- 20500,0.026365477591753
85
- 20750,0.0411790162324905
86
- 21000,0.0182752143591642
87
- 21250,0.0244670584797859
88
- 21500,0.0271810330450535
89
- 21750,0.0361115783452988
90
- 22000,0.0219350345432758
91
- 22250,0.0285932458937168
92
- 22500,0.0203162133693695
93
- 22750,0.0276511423289776
94
- 23000,0.0132249016314745
95
- 23250,0.0206736903637648
96
- 23500,0.0262574516236782
97
- 23750,0.0169588774442673
98
- 24000,0.0314200520515442
99
- 24250,0.0238157659769058
100
- 24500,0.0193928927183151
101
- 24750,0.0290547627955675
102
- 25000,0.0184001661837101
103
- 25250,0.02213329449296
104
- 25500,0.0136252753436565
105
- 25750,0.0179828237742186
106
- 26000,0.0355310514569283
107
- 26250,0.018001502379775
108
- 26500,0.0242008417844772
109
- 26750,0.016164418309927
110
- 27000,0.0177882965654135
111
- 27250,0.0166710373014212
112
- 27500,0.0258242264389992
113
- 27750,0.0342466905713081
114
- 28000,0.0278054904192686
115
- 28250,0.020454116165638
116
- 28500,0.0300905108451843
117
- 28750,0.0254814364016056
118
- 29000,0.0197030957788229
119
- 29250,0.0284833908081055
120
- 29500,0.014562881551683
121
- 29750,0.0159886479377747
122
- 30000,0.0344577208161354
123
- 30250,0.0312892533838749
124
- 30500,0.0229373946785927
125
- 30750,0.0171622224152088
126
- 31000,0.0197725538164377
127
- 31250,0.0162657517939806
128
- 31500,0.0142522044479847
129
- 31750,0.0148013876751065
130
- 32000,0.025500601157546
131
- 32250,0.0166346319019794
132
- 32500,0.0205383319407701
133
- 32750,0.0146346129477024
134
- 33000,0.0211181007325649
135
- 33250,0.0296725053340197
136
- 33500,0.0288714878261089
137
- 33750,0.0138874435797334
138
- 34000,0.0248743556439877
139
- 34250,0.0141851473599672
140
- 34500,0.0252848658710718
141
- 34750,0.0178931225091219
142
- 35000,0.0130898682400584
143
- 35250,0.0115931397303939
144
- 35500,0.0234250612556934
145
- 35750,0.0128768235445023
146
- 36000,0.0169413536787033
147
- 36250,0.0201398637145758
148
- 36500,0.0250215008854866
149
- 36750,0.0219075828790665
150
- 37000,0.0183898508548737
151
- 37250,0.019588889554143
152
- 37500,0.0292202327400446
153
- 37750,0.0163987167179585
154
- 38000,0.0144833931699395
155
- 38250,0.0215383935719728
156
- 38500,0.0184381268918514
157
- 38750,0.0210812538862228
158
- 39000,0.0253688339143991
159
- 39250,0.0227519758045673
160
- 39500,0.0369368530809879
161
- 39750,0.0160970240831375
162
- 40000,0.0261988583952188
163
- 40250,0.0164996907114983
164
- 40500,0.0107930535450578
165
- 40750,0.00939622707664967
166
- 41000,0.0181253775954247
167
- 41250,0.020565377548337
168
- 41500,0.0093222837895155
169
- 41750,0.0237396005541086
170
- 42000,0.020624652504921
171
- 42250,0.0187309104949236
172
- 42500,0.0111600141972303
173
- 42750,0.015045321546495
174
- 43000,0.0142913199961185
175
- 43250,0.0122571792453527
176
- 43500,0.0258257351815701
177
- 43750,0.02132866717875
178
- 44000,0.0159526020288467
179
- 44250,0.0247596241533756
180
- 44500,0.019135007634759
181
- 44750,0.0117857316508889
182
- 45000,0.0167472343891859
183
- 45250,0.0138375330716372
184
- 45500,0.0199624858796597
185
- 45750,0.0169202294200659
186
- 46000,0.0220668632537127
187
- 46250,0.0256760157644749
188
- 46500,0.023376889526844
189
- 46750,0.015702111646533
190
- 47000,0.00732367765158415
191
- 47250,0.0133037976920605
192
- 47500,0.0152414366602898
193
- 47750,0.0210153218358755
194
- 48000,0.0155883701518178
195
- 48250,0.0181764960289001
196
- 48500,0.0122631276026368
197
- 48750,0.0154366279020906
198
- 49000,0.0126272672787309
199
- 49250,0.0163617376238108
200
- 49500,0.00967035163193941
201
- 49750,0.0228679627180099
202
- 50000,0.0153219690546393
203
- 50250,0.023220706731081
204
- 50500,0.00683643249794841
205
- 50750,0.00814869627356529
206
- 51000,0.00921987183392048
207
- 51250,0.0131206875666976
208
- 51500,0.0186909735202789
209
- 51750,0.0187546852976084
210
- 52000,0.016460333019495
211
- 52250,0.0116756521165371
212
- 52500,0.0242307111620903
213
- 52750,0.0169375650584698
214
- 53000,0.0250138565897942
215
- 53250,0.0137153761461377
216
- 53500,0.0249330475926399
217
- 53750,0.016069695353508
218
- 54000,0.0155818546190858
219
- 54250,0.0142799112945795
220
- 54500,0.0187035501003265
221
- 54750,0.0182450339198113
222
- 55000,0.0298508275300264
223
- 55250,0.0159302316606045
224
- 55500,0.0109235905110836
225
- 55750,0.0101459976285696
226
- 56000,0.0174267366528511
227
- 56250,0.0137819238007069
228
- 56500,0.0196770522743464
229
- 56750,0.0218309909105301
230
- 57000,0.00814551673829556
231
- 57250,0.0188653264194727
232
- 57500,0.0104118557646871
233
- 57750,0.0128672821447253
234
- 58000,0.0180737860500813
235
- 58250,0.0128134470432997
236
- 58500,0.0116386357694864
237
- 58750,0.0138751016929746
238
- 59000,0.00804119743406773
239
- 59250,0.0188504103571177
240
- 59500,0.0207543112337589
241
- 59750,0.0102932136505842
242
- 60000,0.0158737506717443
243
- 60250,0.022421021014452
244
- 60500,0.0138980289921165
245
- 60750,0.0174286998808384
246
- 61000,0.0171931218355894
247
- 61250,0.0190867427736521
248
- 61500,0.0243331249803305
249
- 61750,0.0183810405433178
250
- 62000,0.0110008157789707
251
- 62250,0.0225963369011879
252
- 62500,0.0178769212216139
253
- 62750,0.0211460907012224
254
- 63000,0.0196451507508755
255
- 63250,0.025247385725379
256
- 63500,0.012264272198081
257
- 63750,0.0223915576934814
258
- 64000,0.0223147347569466
259
- 64250,0.0171280242502689
260
- 64500,0.0223938636481762
261
- 64750,0.0245739407837391
262
- 65000,0.0170196872204542
263
- 65250,0.0195680633187294
264
- 65500,0.0297231525182724
265
- 65750,0.014296991750598
266
- 66000,0.0149061810225248
267
- 66250,0.0162204243242741
268
- 66500,0.0166388750076294
269
- 66750,0.0309929959475994
270
- 67000,0.00543959345668554
271
- 67250,0.0195787325501442
272
- 67500,0.00983305927366018
273
- 67750,0.0190280470997095
274
- 68000,0.0157865695655346
275
- 68250,0.0129258623346686
276
- 68500,0.0151179721578956
277
- 68750,0.0155658479779959
278
- 69000,0.0167744867503643
279
- 69250,0.0157011542469263
280
- 69500,0.0122998161241412
281
- 69750,0.0158088598400354
282
- 70000,0.00946310814470053
283
- 70250,0.0121819684281945
284
- 70500,0.017717095091939
285
- 70750,0.0219394192099571
286
- 71000,0.0107453716918826
287
- 71250,0.0260140541940927
288
- 71500,0.0151294777169824
289
- 71750,0.012596090324223
290
- 72000,0.0104890521615744
291
- 72250,0.00846360251307488
292
- 72500,0.00763325719162822
293
- 72750,0.0140212699770927
294
- 73000,0.0195035617798567
295
- 73250,0.0108141247183084
296
- 73500,0.0170383471995592
297
- 73750,0.0224394146353006
298
- 74000,0.0144262062385678
299
- 74250,0.00387956923805177
300
- 74500,0.0158057473599911
301
- 74750,0.017770279198885
302
- 75000,0.00916274450719357
303
- 75250,0.0123966634273529
304
- 75500,0.0198220629245043
305
- 75750,0.0167106240987778
306
- 76000,0.00956311635673046
307
- 76250,0.0128496773540974
308
- 76500,0.0260852333158255
309
- 76750,0.00898674689233303
310
- 77000,0.0156727749854326
311
- 77250,0.0140718715265393
312
- 77500,0.0137508492916822
313
- 77750,0.0119758266955614
314
- 78000,0.0129805393517017
315
- 78250,0.0114302476868033
316
- 78500,0.00865038484334946
317
- 78750,0.0184352938085794
318
- 79000,0.00977943371981382
319
- 79250,0.0131393186748028
320
- 79500,0.0169572848826647
321
- 79750,0.00565146515145898
322
- 80000,0.0123953958973289
323
- 80250,0.011800404638052
324
- 80500,0.013363528996706
325
- 80750,0.0213109273463488
326
- 81000,0.00791576970368624
327
- 81250,0.0339761450886726
328
- 81500,0.00917279161512852
329
- 81750,0.0116169452667236
330
- 82000,0.00563255045562983
331
- 82250,0.0241468399763107
332
- 82500,0.00702310493215919
333
- 82750,0.0197079963982105
334
- 83000,0.0251932069659233
335
- 83250,0.0178669150918722
336
- 83500,0.0153062213212252
337
- 83750,0.0122406156733632
338
- 84000,0.00940332561731339
339
- 84250,0.00897864997386932
340
- 84500,0.0088669341057539
341
- 84750,0.0168539173901081
342
- 85000,0.0100771263241768
343
- 85250,0.0162219293415546
344
- 85500,0.018605250865221
345
- 85750,0.0137796280905604
346
- 86000,0.0136929117143154
347
- 86250,0.00253072287887335
348
- 86500,0.00972674414515495
349
- 86750,0.017592029646039
350
- 87000,0.0138086024671793
351
- 87250,0.0069779995828867
352
- 87500,0.00709846755489707
353
- 87750,0.0154324034228921
354
- 88000,0.0111652128398418
355
- 88250,0.00888887234032154
356
- 88500,0.0139657938852906
357
- 88750,0.0119878081604838
358
- 89000,0.0109976017847657
359
- 89250,0.0073125446215272
360
- 89500,0.0209340266883373
361
- 89750,0.0203788764774799
362
- 90000,0.0086817666888237
363
- 90250,0.00725908624008298
364
- 90500,0.00598544534295797
365
- 90750,0.0145876258611679
366
- 91000,0.0126795591786504
367
- 91250,0.0123443659394979
368
- 91500,0.00627651065587997
369
- 91750,0.0099613843485713
370
- 92000,0.015546727925539
371
- 92250,0.0163051821291447
372
- 92500,0.00879416801035404
373
- 92750,0.00909342989325523
374
- 93000,0.00598424486815929
375
- 93250,0.0231871902942657
376
- 93500,0.00725111691281199
377
- 93750,0.00878522731363773
378
- 94000,0.00482694339007139
379
- 94250,0.00697190035134554
380
- 94500,0.0110930856317282
381
- 94750,0.0128715131431818
382
- 95000,0.0114258993417025
383
- 95250,0.013347445987165
384
- 95500,0.0166357383131981
385
- 95750,0.00720312492921948
386
- 96000,0.00874561816453934
387
- 96250,0.0133080519735813
388
- 96500,0.0204655658453703
389
- 96750,0.0152420289814472
390
- 97000,0.00956281647086144
391
- 97250,0.0060010845772922
392
- 97500,0.00643759081140161
393
- 97750,0.00942252390086651
394
- 98000,0.0114145325496793
395
- 98250,0.0135813243687153
396
- 98500,0.00414276216179132
397
- 98750,0.0214146133512259
398
- 99000,0.0115602007135749
399
- 99250,0.0164517313241959
400
- 99500,0.0072403559461236
401
- 99750,0.0145506206899881
402
- 100000,0.00758413504809141
403
- 100250,0.0125142587348819
404
- 100500,0.0178770199418068
405
- 100750,0.0142890457063913
406
- 101000,0.00854901783168316
407
- 101250,0.0139060821384192
408
- 101500,0.00464110169559717
409
- 101750,0.00823721662163734
410
- 102000,0.00814159493893385
411
- 102250,0.0135433813557029
412
- 102500,0.0083465026691556
413
- 102750,0.00659394869580865
414
- 103000,0.0130173917859793
415
- 103250,0.0129606258124113
416
- 103500,0.00877815578132868
417
- 103750,0.0118684452027082
418
- 104000,0.0100804921239614
419
- 104250,0.0154126202687621
420
- 104500,0.0149000762030482
421
- 104750,0.00987151451408863
422
- 105000,0.00978968106210232
423
- 105250,0.0150252487510443
424
- 105500,0.0142000280320644
425
- 105750,0.00656973384320736
426
- 106000,0.0089690126478672
427
- 106250,0.00328237051144242
428
- 106500,0.00789478328078985
429
- 106750,0.0103156510740519
430
- 107000,0.00625590234994888
431
- 107250,0.00566469226032496
432
- 107500,0.0125135416164994
433
- 107750,0.00467129470780492
434
- 108000,0.0136493993923068
435
- 108250,0.0124281644821167
436
- 108500,0.0138487741351128
437
- 108750,0.0035176407545805
438
- 109000,0.00540004624053836
439
- 109250,0.00694243796169758
440
- 109500,0.00663987407460809
441
- 109750,0.0240002684295177
442
- 110000,0.0101069360971451
443
- 110250,0.00700556533411145
444
- 110500,0.00651262886822224
445
- 110750,0.0132803218439221
446
- 111000,0.00589089561253786
447
- 111250,0.0125560127198696
448
- 111500,0.0206313505768776
449
- 111750,0.0100555857643485
450
- 112000,0.0101702576503158
451
- 112250,0.00860929116606712
452
- 112500,0.0132299773395062
453
- 112750,0.0111416969448328
454
- 113000,0.0131795881316066
455
- 113250,0.00872797891497612
456
- 113500,0.00390258966945112
457
- 113750,0.0031361635774374
458
- 114000,0.0090397922322154
459
- 114250,0.00552543625235558
460
- 114500,0.00710977334529161
461
- 114750,0.00620330730453134
462
- 115000,0.00963316485285759
463
- 115250,0.0158268045634031
464
- 115500,0.00626724679023027
465
- 115750,0.00861696619540453
466
- 116000,0.0111084328964353
467
- 116250,0.0114340921863914
468
- 116500,0.00704412022605538
469
- 116750,0.00633083889260888
470
- 117000,0.00693149957805872
471
- 117250,0.0178363360464573
472
- 117500,0.0147715155035257
473
- 117750,0.00902808271348476
474
- 118000,0.00892758183181286
475
- 118250,0.00670483242720366
476
- 118500,0.011395251378417
477
- 118750,0.00546986190602183
478
- 119000,0.0092676542699337
479
- 119250,0.00479461066424847
480
- 119500,0.0106935258954763
481
- 119750,0.00455024186521769
482
- 120000,0.012267179787159
483
- 120250,0.00522866612300277
484
- 120500,0.01401755400002
485
- 120750,0.00754421669989824
486
- 121000,0.00470469892024994
487
- 121250,0.00263528944924474
488
- 121500,0.00464372336864471
489
- 121750,0.00638889381662011
490
- 122000,0.00766867864876986
491
- 122250,0.0109868571162224
492
- 122500,0.0114285778254271
493
- 122750,0.00994583684951067
494
- 123000,0.00710724294185638
495
- 123250,0.018058218061924
496
- 123500,0.00433817086741328
497
- 123750,0.00958674401044846
498
- 124000,0.00790040567517281
499
- 124250,0.0111565012484789
500
- 124500,0.0087413564324379
501
- 124750,0.00318941287696362
502
- 125000,0.0131127815693617
503
- 125250,0.00226907734759152
504
- 125500,0.00739215547218919
505
- 125750,0.00890939030796289
506
- 126000,0.00806392915546894
507
- 126250,0.00660573691129684
508
- 126500,0.00495407776907086
509
- 126750,0.00671287253499031
510
- 127000,0.0103982714936137
511
- 127250,0.0040901224128902
512
- 127500,0.00866457633674145
513
- 127750,0.0118970824405551
514
- 128000,0.00429999455809593
515
- 128250,0.00876860041171312
516
- 128500,0.00857545156031847
517
- 128750,0.00306878588162363
518
- 129000,0.00783287547528744
519
- 129250,0.00890291761606932
520
- 129500,0.0026889881119132
521
- 129750,0.0108866654336452
522
- 130000,0.0123450383543968
523
- 130250,0.00442803371697664
524
- 130500,0.0102869970723987
525
- 130750,0.00574492616578937
526
- 131000,0.0141308568418026
527
- 131250,0.0103325974196196
528
- 131500,0.0072377328760922
529
- 131750,0.0061816368252039
530
- 132000,0.00732836313545704
531
- 132250,0.00656922487542033
532
- 132500,0.00621314067393541
533
- 132750,0.008244713768363
534
- 133000,0.0190647430717945
535
- 133250,0.00824970006942749
536
- 133500,0.0165427252650261
537
- 133750,0.00404272554442287
538
- 134000,0.0123105738312006
539
- 134250,0.00211115484125912
540
- 134500,0.0100123398005962
541
- 134750,0.00712257949635386
542
- 135000,0.00735276937484741
543
- 135250,0.00601832382380962
544
- 135500,0.0101933050900698
545
- 135750,0.00438989512622356
546
- 136000,0.00703473901376128
547
- 136250,0.00421222252771258
548
- 136500,0.00747972261160612
549
- 136750,0.00781664624810219
550
- 137000,0.00334988045506179
551
- 137250,0.00512576103210449
552
- 137500,0.00457540573552251
553
- 137750,0.00810420699417591
554
- 138000,0.0155664328485727
555
- 138250,0.00325041124597192
556
- 138500,0.00902775209397078
557
- 138750,0.00582149112597108
558
- 139000,0.00628531211987138
559
- 139250,0.00974354986101389
560
- 139500,0.00699424277991056
561
- 139750,0.0116820987313986
562
- 140000,0.0040350342169404
563
- 140250,0.00367987621575594
564
- 140500,0.00849070958793163
565
- 140750,0.0125005636364222
566
- 141000,0.00857609417289496
567
- 141250,0.00422609690576792
568
- 141500,0.0135511830449104
569
- 141750,0.00641574431210756
570
- 142000,0.00786767154932022
571
- 142250,0.00515902321785688
572
- 142500,0.00376095669344068
573
- 142750,0.00316811888478696
574
- 143000,0.0142639232799411
575
- 143250,0.010791152715683
576
- 143500,0.00339762796647847
577
- 143750,0.00538199068978429
578
- 144000,0.00940855406224728
579
- 144250,0.0136599931865931
580
- 144500,0.00447291322052479
581
- 144750,0.0046997768804431
582
- 145000,0.00632298365235329
583
- 145250,0.00658218376338482
584
- 145500,0.00440026680007577
585
- 145750,0.00342981959693134
586
- 146000,0.00212057679891586
587
- 146250,0.00497672613710165
588
- 146500,0.0070713791064918
589
- 146750,0.00436870707198978
590
- 147000,0.00315663125365973
591
- 147250,0.00536526972427964
592
- 147500,0.00536233698949218
593
- 147750,0.00521381665021181
594
- 148000,0.00207849009893835
595
- 148250,0.00483316881582141
596
- 148500,0.0111163007095456
597
- 148750,0.0055245510302484
598
- 149000,0.00546429073438048
599
- 149250,0.00733712874352932
600
- 149500,0.00471039395779371
601
- 149750,0.00878884457051754
602
- 150000,0.00372292008250952
603
- 150250,0.00635994179174304
604
- 150500,0.00917862728238106
605
- 150750,0.0108220754191279
606
- 151000,0.00445558922365308
607
- 151250,0.00656689237803221
608
- 151500,0.00481499498710036
609
- 151750,0.0062879347242415
610
- 152000,0.00657450780272484
611
- 152250,0.00523933628574014
612
- 152500,0.00864152610301971
613
- 152750,0.00272159278392792
614
- 153000,0.0101496782153845
615
- 153250,0.00498205749318004
616
- 153500,0.0102331517264247
617
- 153750,0.00289264298044145
618
- 154000,0.00644394569098949
619
- 154250,0.00709045119583607
620
- 154500,0.00844221375882626
621
- 154750,0.00466649560257793
622
- 155000,0.00753895612433553
623
- 155250,0.00790270324796438
624
- 155500,0.00437433738261461
625
- 155750,0.00400823261588812
626
- 156000,0.00366482068784535
627
- 156250,0.00391580816358328
628
- 156500,0.00400443840771914
629
- 156750,0.00404176488518715
630
- 157000,0.00499014649540186
631
- 157250,0.0172605812549591
632
- 157500,0.0102259423583746
633
- 157750,0.00238762702792883
634
- 158000,0.00315944105386734
635
- 158250,0.00168710923753679
636
- 158500,0.0019604405388236
637
- 158750,0.00251147709786892
638
- 159000,0.00650985445827246
639
- 159250,0.00546598341315985
640
- 159500,0.00425415113568306
641
- 159750,0.00161121017299593
642
- 160000,0.00230288645252585
643
- 160250,0.00643144082278013
644
- 160500,0.00432394817471504
645
- 160750,0.00634075421839953
646
- 161000,0.00571991130709648
647
- 161250,0.0144351711496711
648
- 161500,0.00417742412537336
649
- 161750,0.00902252551168203
650
- 162000,0.00813286192715168
651
- 162250,0.00462814979255199
652
- 162500,0.00248837098479271
653
- 162750,0.00694522261619568
654
- 163000,0.00748669356107712
655
- 163250,0.0103418631479144
656
- 163500,0.00474565383046865
657
- 163750,0.00914457440376282
658
- 164000,0.00375485350377858
659
- 164250,0.00331662711687386
660
- 164500,0.00435616914182901
661
- 164750,0.00325128878466785
662
- 165000,0.00289723044261336
663
- 165250,0.00836396217346191
664
- 165500,0.00769220851361752
665
- 165750,0.00145601853728294
666
- 166000,0.00369948521256447
667
- 166250,0.00676249712705612
668
- 166500,0.00504903821274638
669
- 166750,0.00344920065253973
670
- 167000,0.00418912898749113
671
- 167250,0.00713308062404394
672
- 167500,0.00454435963183641
673
- 167750,0.0152177475392818
674
- 168000,0.00482255965471268
675
- 168250,0.00824730191379786
676
- 168500,0.00942600890994072
677
- 168750,0.00601507490500808
678
- 169000,0.00711566489189863
679
- 169250,0.00288966251537204
680
- 169500,0.00614543166011572
681
- 169750,0.00461590569466352
682
- 170000,0.0040288707241416
683
- 170250,0.00465019326657057
684
- 170500,0.0058364924043417
685
- 170750,0.0111788678914309
686
- 171000,0.0101717775687575
687
- 171250,0.00669318437576294
688
- 171500,0.00241118902340531
689
- 171750,0.00748110422864556
690
- 172000,0.00324534485116601
691
- 172250,0.0139279589056969
692
- 172500,0.00669022276997566
693
- 172750,0.0109275430440903
694
- 173000,0.00496043357998133
695
- 173250,0.00455513503402472
696
- 173500,0.0049431505613029
697
- 173750,0.00228843558579683
698
- 174000,0.00291855679824948
699
- 174250,0.00344458501785994
700
- 174500,0.00427282229065895
701
- 174750,0.00224346201866865
702
- 175000,0.00493356585502625
703
- 175250,0.00907189305871725
704
- 175500,0.00446609035134316
705
- 175750,0.00691913440823555
706
- 176000,0.00316060450859368
707
- 176250,0.00359506718814373
708
- 176500,0.00170307909138501
709
- 176750,0.00282602733932436
710
- 177000,0.00477674370631576
711
- 177250,0.00438745226711035
712
- 177500,0.008196079172194
713
- 177750,0.028399832546711
714
- 178000,0.00717926071956754
715
- 178250,0.00196872535161674
716
- 178500,0.00710827112197876
717
- 178750,0.00394357228651643
718
- 179000,0.00349363568238914
719
- 179250,0.000701560988090932
720
- 179500,0.0027123533654958
721
- 179750,0.0046698534861207
722
- 180000,0.00579128507524729
723
- 180250,0.00581067427992821
724
- 180500,0.0047798277810216
725
- 180750,0.00667576305568218
726
- 181000,0.00395611580461264
727
- 181250,0.00492685707286
728
- 181500,0.00745255220681429
729
- 181750,0.0131707303225994
730
- 182000,0.00387760531157255
731
- 182250,0.00864568073302507
732
- 182500,0.00274329842068255
733
- 182750,0.00596647802740335
734
- 183000,0.004488087259233
735
- 183250,0.00247273012064397
736
- 183500,0.00201883772388101
737
- 183750,0.0042853094637394
738
- 184000,0.00134791061282158
739
- 184250,0.00579879945144057
740
- 184500,0.00602423865348101
741
- 184750,0.00924103334546089
742
- 185000,0.00235534040257335
743
- 185250,0.00802786089479923
744
- 185500,0.00819941889494658
745
- 185750,0.00423980969935656
746
- 186000,0.0051832776516676
747
- 186250,0.0034146779216826
748
- 186500,0.00605300348252058
749
- 186750,0.00732398964464664
750
- 187000,0.00114329461939633
751
- 187250,0.00642803031951189
752
- 187500,0.000934973184484988
753
- 187750,0.00141588214319199
754
- 188000,0.00279860408045351
755
- 188250,0.00264930352568626
756
- 188500,0.00532305892556906
757
- 188750,0.00219094636850059
758
- 189000,0.0098413685336709
759
- 189250,0.00171840551774949
760
- 189500,0.00470842607319355
761
- 189750,0.00402260012924671
762
- 190000,0.00832562707364559
763
- 190250,0.00488234404474497
764
- 190500,0.00468898843973875
765
- 190750,0.00359549792483449
766
- 191000,0.00255341292358935
767
- 191250,0.00728059187531471
768
- 191500,0.00449383538216352
769
- 191750,0.00242296862415969
770
- 192000,0.00171702424995601
771
- 192250,0.00454688305035234
772
- 192500,0.00542865041643381
773
- 192750,0.00283833267167211
774
- 193000,0.00262197386473417
775
- 193250,0.00628780666738749
776
- 193500,0.0061873602680862
777
- 193750,0.00353108532726765
778
- 194000,0.0114784147590399
779
- 194250,0.00208971230313182
780
- 194500,0.00169187935534865
781
- 194750,0.00185852451249957
782
- 195000,0.00283539621159434
783
- 195250,0.0056375372223556
784
- 195500,0.00181959476321936
785
- 195750,0.0037946121301502
786
- 196000,0.00441271159797907
787
- 196250,0.00334653444588184
788
- 196500,0.00304620480164886
789
- 196750,0.00756439147517085
790
- 197000,0.00326189352199435
791
- 197250,0.00278747989796102
792
- 197500,0.00410604570060968
793
- 197750,0.0102813914418221
794
- 198000,0.00206433120183647
795
- 198250,0.00723177986219525
796
- 198500,0.00193094939459115
797
- 198750,0.00181513070128858
798
- 199000,0.00131357798818499
799
- 199250,0.00225170888006687
800
- 199500,0.00180370500311255
801
- 199750,0.00738364644348621
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
training_curves.png CHANGED