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coder-model

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  1. __pycache__/predict.cpython-311.pyc +0 -0
  2. config.json +1 -1
  3. model.pt +2 -2
  4. predict.py +20 -60
  5. train.log +276 -277
__pycache__/predict.cpython-311.pyc CHANGED
Binary files a/__pycache__/predict.cpython-311.pyc and b/__pycache__/predict.cpython-311.pyc differ
 
config.json CHANGED
@@ -1 +1 @@
1
- {"in_channels": 24, "out_channels": 12, "channels": [32, 64, 128, 256], "context_len": 8, "model_class": "FlowWarpAttnUNet"}
 
1
+ {"in_channels": 24, "channels": [32, 64, 128, 256], "context_len": 8, "model_class": "FlowWarpAttnUNet"}
model.pt CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
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- oid sha256:06d08eedaeed225b294d854f97c1a00cb1df65efaee9394c6e0ddb722b227e49
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- size 15223690
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:6d623d95dfb97c0eb9fd0da6805c669084a7033c0dee4bb734d929b93add4bf5
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+ size 15223306
predict.py CHANGED
@@ -1,4 +1,4 @@
1
- """Inference for 2-frame simultaneous predictor with TTA."""
2
  import json
3
  import numpy as np
4
  import torch
@@ -10,23 +10,14 @@ from flow_warp_attn_model import FlowWarpAttnUNet
10
  def load_model(model_dir: str):
11
  with open(f"{model_dir}/config.json") as f:
12
  config = json.load(f)
13
- model = FlowWarpAttnUNet(
14
- in_channels=config["in_channels"],
15
- channels=config["channels"],
16
- out_channels=config.get("out_channels", 6)
17
- )
18
  sd = torch.load(f"{model_dir}/model.pt", map_location="cpu", weights_only=True)
19
  sd = {k: v.float() for k, v in sd.items()}
20
  model.load_state_dict(sd)
21
  model.eval()
22
  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
23
  model = model.to(device)
24
- return {
25
- "model": model,
26
- "device": device,
27
- "context_len": config["context_len"],
28
- "cached_pred2": None,
29
- }
30
 
31
 
32
  def _prepare_input(context_frames, context_len):
@@ -43,57 +34,26 @@ def _prepare_input(context_frames, context_len):
43
  return context, last_frame
44
 
45
 
46
- def _run_model_tta(model, device, ctx, last):
47
- """Run model with TTA (horizontal flip) and return both predictions."""
48
- with torch.no_grad():
49
- ctx_t = torch.from_numpy(ctx).to(device)
50
- last_t = torch.from_numpy(last).to(device)
51
- preds1, _ = model(ctx_t, last_t)
52
-
53
- # Flipped
54
- ctx_f = torch.from_numpy(ctx[:, :, :, ::-1].copy()).to(device)
55
- last_f = torch.from_numpy(last[:, :, :, ::-1].copy()).to(device)
56
- preds2, _ = model(ctx_f, last_f)
57
-
58
- # Average normal and flipped-back predictions
59
- pred1 = (preds1[0] + preds2[0].flip(-1)) / 2.0
60
- pred2 = (preds1[1] + preds2[1].flip(-1)) / 2.0
61
-
62
- return pred1, pred2
63
-
64
-
65
  def predict_next_frame(model_dict, context_frames: np.ndarray) -> np.ndarray:
66
  model = model_dict["model"]
67
  device = model_dict["device"]
68
  context_len = model_dict["context_len"]
69
 
70
- # Determine if this is an even or odd call
71
- # Even-length context (8, 10, 12, 14): run model, return pred1, cache pred2
72
- # Odd-length context (9, 11, 13, 15): return cached pred2
73
- n = len(context_frames)
74
-
75
- if n % 2 == 0:
76
- # Run model
77
- ctx, last = _prepare_input(context_frames, context_len)
78
- pred1, pred2 = _run_model_tta(model, device, ctx, last)
79
-
80
- # Cache pred2
81
- pred2_np = pred2[0].cpu().numpy()
82
- pred2_np = np.transpose(pred2_np, (1, 2, 0))
83
- model_dict["cached_pred2"] = (pred2_np * 255.0).clip(0, 255).astype(np.uint8)
84
 
85
- # Return pred1
86
- pred1_np = pred1[0].cpu().numpy()
87
- pred1_np = np.transpose(pred1_np, (1, 2, 0))
88
- return (pred1_np * 255.0).clip(0, 255).astype(np.uint8)
89
- else:
90
- # Return cached pred2
91
- if model_dict["cached_pred2"] is not None:
92
- return model_dict["cached_pred2"]
93
- else:
94
- # Fallback: run model on context minus last frame
95
- ctx, last = _prepare_input(context_frames[:-1], context_len)
96
- pred1, pred2 = _run_model_tta(model, device, ctx, last)
97
- pred2_np = pred2[0].cpu().numpy()
98
- pred2_np = np.transpose(pred2_np, (1, 2, 0))
99
- return (pred2_np * 255.0).clip(0, 255).astype(np.uint8)
 
1
+ """Inference for AR curriculum model + TTA."""
2
  import json
3
  import numpy as np
4
  import torch
 
10
  def load_model(model_dir: str):
11
  with open(f"{model_dir}/config.json") as f:
12
  config = json.load(f)
13
+ model = FlowWarpAttnUNet(in_channels=config["in_channels"], channels=config["channels"])
 
 
 
 
14
  sd = torch.load(f"{model_dir}/model.pt", map_location="cpu", weights_only=True)
15
  sd = {k: v.float() for k, v in sd.items()}
16
  model.load_state_dict(sd)
17
  model.eval()
18
  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
19
  model = model.to(device)
20
+ return {"model": model, "device": device, "context_len": config["context_len"]}
 
 
 
 
 
21
 
22
 
23
  def _prepare_input(context_frames, context_len):
 
34
  return context, last_frame
35
 
36
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
37
  def predict_next_frame(model_dict, context_frames: np.ndarray) -> np.ndarray:
38
  model = model_dict["model"]
39
  device = model_dict["device"]
40
  context_len = model_dict["context_len"]
41
 
42
+ ctx, last = _prepare_input(context_frames, context_len)
43
+ with torch.no_grad():
44
+ ctx_t = torch.from_numpy(ctx).to(device)
45
+ last_t = torch.from_numpy(last).to(device)
46
+ pred1, _ = model(ctx_t, last_t)
 
 
 
 
 
 
 
 
 
47
 
48
+ flipped_frames = context_frames[:, :, ::-1, :].copy()
49
+ ctx_f, last_f = _prepare_input(flipped_frames, context_len)
50
+ with torch.no_grad():
51
+ ctx_ft = torch.from_numpy(ctx_f).to(device)
52
+ last_ft = torch.from_numpy(last_f).to(device)
53
+ pred2, _ = model(ctx_ft, last_ft)
54
+ pred2 = pred2.flip(-1)
55
+
56
+ pred = (pred1 + pred2) / 2.0
57
+ pred_np = pred[0].cpu().numpy()
58
+ pred_np = np.transpose(pred_np, (1, 2, 0))
59
+ return (pred_np * 255.0).clip(0, 255).astype(np.uint8)
 
 
 
train.log CHANGED
@@ -1,277 +1,276 @@
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- [00:07:53] Extended head.weight from 6 to 12 output channels
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- [00:07:53] Extended head.bias from 6 to 12 output channels
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- [00:07:54] Model: 2-frame FlowWarpAttnUNet (12ch out), 7,596,940 params
4
- [00:07:54] === Phase 1: 2-frame simultaneous (120 epochs) ===
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- [00:07:59] Train: 44213, Val: 5434
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- [00:08:51] P1 Ep 1/120 | Train: 0.061978 | Val: 0.077449 | LR: 1.00e-04
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- [00:08:51] -> Saved (val=0.077449)
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- [00:09:43] P1 Ep 2/120 | Train: 0.053971 | Val: 0.075218 | LR: 9.99e-05
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- [00:09:43] -> Saved (val=0.075218)
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- [00:10:33] P1 Ep 3/120 | Train: 0.051406 | Val: 0.073175 | LR: 9.98e-05
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- [00:10:33] -> Saved (val=0.073175)
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- [00:11:27] P1 Ep 4/120 | Train: 0.049921 | Val: 0.073100 | LR: 9.97e-05
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- [00:11:27] -> Saved (val=0.073100)
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- [00:12:19] P1 Ep 5/120 | Train: 0.048883 | Val: 0.072808 | LR: 9.96e-05
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- [00:12:19] -> Saved (val=0.072808)
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- [00:13:13] P1 Ep 6/120 | Train: 0.048200 | Val: 0.073129 | LR: 9.94e-05
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- [00:14:02] P1 Ep 7/120 | Train: 0.047661 | Val: 0.072025 | LR: 9.92e-05
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- [00:14:02] -> Saved (val=0.072025)
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- [00:14:52] P1 Ep 8/120 | Train: 0.047149 | Val: 0.072146 | LR: 9.89e-05
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- [00:19:18] -> Saved (val=0.071034)
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- [00:26:08] -> Saved (val=0.071014)
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- [00:27:04] P1 Ep 22/120 | Train: 0.042821 | Val: 0.071219 | LR: 9.20e-05
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- [01:48:49] P1 Ep 114/120 | Train: 0.032485 | Val: 0.073207 | LR: 1.61e-06
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- [01:49:45] P1 Ep 115/120 | Train: 0.032484 | Val: 0.073184 | LR: 1.42e-06
131
- [01:50:35] P1 Ep 116/120 | Train: 0.032462 | Val: 0.073198 | LR: 1.27e-06
132
- [01:51:30] P1 Ep 117/120 | Train: 0.032458 | Val: 0.073201 | LR: 1.15e-06
133
- [01:52:24] P1 Ep 118/120 | Train: 0.032469 | Val: 0.073226 | LR: 1.07e-06
134
- [01:53:20] P1 Ep 119/120 | Train: 0.032486 | Val: 0.073221 | LR: 1.02e-06
135
- [01:54:17] P1 Ep 120/120 | Train: 0.032437 | Val: 0.073237 | LR: 1.00e-06
136
- [01:54:17] === Phase 2: 2-pair AR (80 epochs) ===
137
- [01:54:22] Train: 11098, Val: 1364
138
- [01:54:55] P2 Ep 1/80 | Train: 0.054557 | Val: 0.106498 | LR: 3.00e-05 | TF: 0.30
139
- [01:54:55] -> Saved P2 (val=0.106498)
140
- [01:55:29] P2 Ep 2/80 | Train: 0.054574 | Val: 0.106666 | LR: 3.00e-05 | TF: 0.30
141
- [01:56:03] P2 Ep 3/80 | Train: 0.053318 | Val: 0.107518 | LR: 2.99e-05 | TF: 0.29
142
- [01:56:37] P2 Ep 4/80 | Train: 0.052657 | Val: 0.107697 | LR: 2.98e-05 | TF: 0.29
143
- [01:57:11] P2 Ep 5/80 | Train: 0.051832 | Val: 0.107233 | LR: 2.97e-05 | TF: 0.28
144
- [01:57:44] P2 Ep 6/80 | Train: 0.051541 | Val: 0.106448 | LR: 2.96e-05 | TF: 0.28
145
- [01:57:44] -> Saved P2 (val=0.106448)
146
- [01:58:18] P2 Ep 7/80 | Train: 0.051457 | Val: 0.107375 | LR: 2.95e-05 | TF: 0.28
147
- [01:58:52] P2 Ep 8/80 | Train: 0.051690 | Val: 0.107256 | LR: 2.93e-05 | TF: 0.27
148
- [01:59:25] P2 Ep 9/80 | Train: 0.050669 | Val: 0.107383 | LR: 2.91e-05 | TF: 0.27
149
- [01:59:59] P2 Ep 10/80 | Train: 0.051103 | Val: 0.107907 | LR: 2.89e-05 | TF: 0.27
150
- [02:00:32] P2 Ep 11/80 | Train: 0.050864 | Val: 0.107474 | LR: 2.87e-05 | TF: 0.26
151
- [02:01:05] P2 Ep 12/80 | Train: 0.050607 | Val: 0.107356 | LR: 2.84e-05 | TF: 0.26
152
- [02:01:40] P2 Ep 13/80 | Train: 0.050188 | Val: 0.107834 | LR: 2.82e-05 | TF: 0.26
153
- [02:02:13] P2 Ep 14/80 | Train: 0.049680 | Val: 0.108136 | LR: 2.79e-05 | TF: 0.25
154
- [02:02:45] P2 Ep 15/80 | Train: 0.049584 | Val: 0.108029 | LR: 2.76e-05 | TF: 0.25
155
- [02:03:18] P2 Ep 16/80 | Train: 0.049773 | Val: 0.108143 | LR: 2.72e-05 | TF: 0.24
156
- [02:03:52] P2 Ep 17/80 | Train: 0.049839 | Val: 0.107671 | LR: 2.69e-05 | TF: 0.24
157
- [02:04:25] P2 Ep 18/80 | Train: 0.049650 | Val: 0.108371 | LR: 2.65e-05 | TF: 0.24
158
- [02:04:59] P2 Ep 19/80 | Train: 0.049281 | Val: 0.107904 | LR: 2.61e-05 | TF: 0.23
159
- [02:05:32] P2 Ep 20/80 | Train: 0.049104 | Val: 0.107936 | LR: 2.58e-05 | TF: 0.23
160
- [02:06:06] P2 Ep 21/80 | Train: 0.049169 | Val: 0.108025 | LR: 2.53e-05 | TF: 0.22
161
- [02:06:39] P2 Ep 22/80 | Train: 0.048988 | Val: 0.108295 | LR: 2.49e-05 | TF: 0.22
162
- [02:07:13] P2 Ep 23/80 | Train: 0.048794 | Val: 0.108466 | LR: 2.45e-05 | TF: 0.22
163
- [02:07:45] P2 Ep 24/80 | Train: 0.049192 | Val: 0.108640 | LR: 2.40e-05 | TF: 0.21
164
- [02:08:19] P2 Ep 25/80 | Train: 0.048759 | Val: 0.108915 | LR: 2.36e-05 | TF: 0.21
165
- [02:08:53] P2 Ep 26/80 | Train: 0.048250 | Val: 0.109006 | LR: 2.31e-05 | TF: 0.21
166
- [02:09:26] P2 Ep 27/80 | Train: 0.048639 | Val: 0.109548 | LR: 2.26e-05 | TF: 0.20
167
- [02:10:00] P2 Ep 28/80 | Train: 0.048423 | Val: 0.109665 | LR: 2.21e-05 | TF: 0.20
168
- [02:10:32] P2 Ep 29/80 | Train: 0.047949 | Val: 0.109045 | LR: 2.16e-05 | TF: 0.20
169
- [02:11:06] P2 Ep 30/80 | Train: 0.048071 | Val: 0.108845 | LR: 2.10e-05 | TF: 0.19
170
- [02:11:40] P2 Ep 31/80 | Train: 0.047972 | Val: 0.109285 | LR: 2.05e-05 | TF: 0.19
171
- [02:12:14] P2 Ep 32/80 | Train: 0.047973 | Val: 0.108996 | LR: 2.00e-05 | TF: 0.18
172
- [02:12:48] P2 Ep 33/80 | Train: 0.047556 | Val: 0.109569 | LR: 1.94e-05 | TF: 0.18
173
- [02:13:22] P2 Ep 34/80 | Train: 0.047713 | Val: 0.110014 | LR: 1.89e-05 | TF: 0.18
174
- [02:13:56] P2 Ep 35/80 | Train: 0.047856 | Val: 0.110129 | LR: 1.83e-05 | TF: 0.17
175
- [02:14:29] P2 Ep 36/80 | Train: 0.047775 | Val: 0.109471 | LR: 1.78e-05 | TF: 0.17
176
- [02:15:03] P2 Ep 37/80 | Train: 0.047412 | Val: 0.109849 | LR: 1.72e-05 | TF: 0.17
177
- [02:15:36] P2 Ep 38/80 | Train: 0.047392 | Val: 0.109965 | LR: 1.66e-05 | TF: 0.16
178
- [02:16:07] P2 Ep 39/80 | Train: 0.047320 | Val: 0.109771 | LR: 1.61e-05 | TF: 0.16
179
- [02:16:41] P2 Ep 40/80 | Train: 0.047311 | Val: 0.109923 | LR: 1.55e-05 | TF: 0.15
180
- [02:17:14] P2 Ep 41/80 | Train: 0.046883 | Val: 0.110259 | LR: 1.49e-05 | TF: 0.15
181
- [02:17:48] P2 Ep 42/80 | Train: 0.047239 | Val: 0.109966 | LR: 1.44e-05 | TF: 0.15
182
- [02:18:21] P2 Ep 43/80 | Train: 0.047145 | Val: 0.110113 | LR: 1.38e-05 | TF: 0.14
183
- [02:18:54] P2 Ep 44/80 | Train: 0.046842 | Val: 0.110258 | LR: 1.32e-05 | TF: 0.14
184
- [02:19:28] P2 Ep 45/80 | Train: 0.047189 | Val: 0.110256 | LR: 1.27e-05 | TF: 0.13
185
- [02:20:01] P2 Ep 46/80 | Train: 0.046912 | Val: 0.110545 | LR: 1.21e-05 | TF: 0.13
186
- [02:20:31] P2 Ep 47/80 | Train: 0.046719 | Val: 0.110554 | LR: 1.16e-05 | TF: 0.13
187
- [02:21:04] P2 Ep 48/80 | Train: 0.046622 | Val: 0.110318 | LR: 1.10e-05 | TF: 0.12
188
- [02:21:37] P2 Ep 49/80 | Train: 0.046894 | Val: 0.111087 | LR: 1.05e-05 | TF: 0.12
189
- [02:22:11] P2 Ep 50/80 | Train: 0.046511 | Val: 0.110787 | LR: 9.95e-06 | TF: 0.12
190
- [02:22:44] P2 Ep 51/80 | Train: 0.046626 | Val: 0.110765 | LR: 9.43e-06 | TF: 0.11
191
- [02:23:17] P2 Ep 52/80 | Train: 0.046520 | Val: 0.110935 | LR: 8.92e-06 | TF: 0.11
192
- [02:23:51] P2 Ep 53/80 | Train: 0.046424 | Val: 0.110928 | LR: 8.41e-06 | TF: 0.10
193
- [02:24:24] P2 Ep 54/80 | Train: 0.046440 | Val: 0.110769 | LR: 7.92e-06 | TF: 0.10
194
- [02:24:58] P2 Ep 55/80 | Train: 0.046489 | Val: 0.110981 | LR: 7.44e-06 | TF: 0.10
195
- [02:25:31] P2 Ep 56/80 | Train: 0.046320 | Val: 0.111142 | LR: 6.98e-06 | TF: 0.09
196
- [02:26:01] P2 Ep 57/80 | Train: 0.046366 | Val: 0.110924 | LR: 6.52e-06 | TF: 0.09
197
- [02:26:32] P2 Ep 58/80 | Train: 0.046442 | Val: 0.110997 | LR: 6.08e-06 | TF: 0.09
198
- [02:27:05] P2 Ep 59/80 | Train: 0.046215 | Val: 0.110918 | LR: 5.66e-06 | TF: 0.08
199
- [02:27:37] P2 Ep 60/80 | Train: 0.046221 | Val: 0.111078 | LR: 5.25e-06 | TF: 0.08
200
- [02:28:08] P2 Ep 61/80 | Train: 0.046320 | Val: 0.111255 | LR: 4.85e-06 | TF: 0.07
201
- [02:28:41] P2 Ep 62/80 | Train: 0.046290 | Val: 0.111131 | LR: 4.47e-06 | TF: 0.07
202
- [02:29:14] P2 Ep 63/80 | Train: 0.046355 | Val: 0.111194 | LR: 4.11e-06 | TF: 0.07
203
- [02:29:47] P2 Ep 64/80 | Train: 0.046299 | Val: 0.111137 | LR: 3.77e-06 | TF: 0.06
204
- [02:30:21] P2 Ep 65/80 | Train: 0.046351 | Val: 0.111013 | LR: 3.44e-06 | TF: 0.06
205
- [02:30:54] P2 Ep 66/80 | Train: 0.046255 | Val: 0.111259 | LR: 3.14e-06 | TF: 0.06
206
- [02:31:28] P2 Ep 67/80 | Train: 0.046359 | Val: 0.111343 | LR: 2.85e-06 | TF: 0.05
207
- [02:32:01] P2 Ep 68/80 | Train: 0.046468 | Val: 0.111270 | LR: 2.58e-06 | TF: 0.05
208
- [02:32:35] P2 Ep 69/80 | Train: 0.046102 | Val: 0.111267 | LR: 2.33e-06 | TF: 0.05
209
- [02:33:09] P2 Ep 70/80 | Train: 0.046351 | Val: 0.111322 | LR: 2.10e-06 | TF: 0.04
210
- [02:33:42] P2 Ep 71/80 | Train: 0.046254 | Val: 0.111232 | LR: 1.90e-06 | TF: 0.04
211
- [02:34:15] P2 Ep 72/80 | Train: 0.046285 | Val: 0.111315 | LR: 1.71e-06 | TF: 0.03
212
- [02:34:49] P2 Ep 73/80 | Train: 0.046287 | Val: 0.111381 | LR: 1.54e-06 | TF: 0.03
213
- [02:35:23] P2 Ep 74/80 | Train: 0.046461 | Val: 0.111264 | LR: 1.40e-06 | TF: 0.03
214
- [02:35:56] P2 Ep 75/80 | Train: 0.046390 | Val: 0.111400 | LR: 1.28e-06 | TF: 0.02
215
- [02:36:29] P2 Ep 76/80 | Train: 0.046424 | Val: 0.111390 | LR: 1.18e-06 | TF: 0.02
216
- [02:37:03] P2 Ep 77/80 | Train: 0.046389 | Val: 0.111377 | LR: 1.10e-06 | TF: 0.02
217
- [02:37:37] P2 Ep 78/80 | Train: 0.046533 | Val: 0.111417 | LR: 1.04e-06 | TF: 0.01
218
- [02:38:02] P2 Ep 79/80 | Train: 0.046486 | Val: 0.111412 | LR: 1.01e-06 | TF: 0.01
219
- [02:38:31] P2 Ep 80/80 | Train: 0.046501 | Val: 0.111431 | LR: 1.00e-06 | TF: 0.00
220
- [02:38:31] === Phase 3: 4-pair AR (50 epochs) ===
221
- [02:38:36] Train: 5549, Val: 682
222
- [02:39:22] P3 Ep 1/50 | Train: 0.092983 | Val: 0.161518 | LR: 9.99e-06
223
- [02:39:22] -> Saved P3 (val=0.161518)
224
- [02:40:08] P3 Ep 2/50 | Train: 0.090956 | Val: 0.159641 | LR: 9.96e-06
225
- [02:40:08] -> Saved P3 (val=0.159641)
226
- [02:40:54] P3 Ep 3/50 | Train: 0.089849 | Val: 0.160089 | LR: 9.92e-06
227
- [02:41:39] P3 Ep 4/50 | Train: 0.088783 | Val: 0.160196 | LR: 9.86e-06
228
- [02:42:24] P3 Ep 5/50 | Train: 0.087803 | Val: 0.159608 | LR: 9.78e-06
229
- [02:42:24] -> Saved P3 (val=0.159608)
230
- [02:43:10] P3 Ep 6/50 | Train: 0.086842 | Val: 0.159242 | LR: 9.68e-06
231
- [02:43:10] -> Saved P3 (val=0.159242)
232
- [02:43:55] P3 Ep 7/50 | Train: 0.086485 | Val: 0.158938 | LR: 9.57e-06
233
- [02:43:55] -> Saved P3 (val=0.158938)
234
- [02:44:40] P3 Ep 8/50 | Train: 0.085548 | Val: 0.159388 | LR: 9.44e-06
235
- [02:45:27] P3 Ep 9/50 | Train: 0.085003 | Val: 0.159269 | LR: 9.30e-06
236
- [02:46:13] P3 Ep 10/50 | Train: 0.084472 | Val: 0.159734 | LR: 9.14e-06
237
- [02:46:59] P3 Ep 11/50 | Train: 0.083980 | Val: 0.159817 | LR: 8.97e-06
238
- [02:47:45] P3 Ep 12/50 | Train: 0.083577 | Val: 0.160148 | LR: 8.78e-06
239
- [02:48:30] P3 Ep 13/50 | Train: 0.082901 | Val: 0.160434 | LR: 8.58e-06
240
- [02:49:16] P3 Ep 14/50 | Train: 0.082547 | Val: 0.159832 | LR: 8.37e-06
241
- [02:50:02] P3 Ep 15/50 | Train: 0.081991 | Val: 0.160071 | LR: 8.15e-06
242
- [02:50:47] P3 Ep 16/50 | Train: 0.081574 | Val: 0.161300 | LR: 7.91e-06
243
- [02:51:33] P3 Ep 17/50 | Train: 0.081306 | Val: 0.160231 | LR: 7.67e-06
244
- [02:52:19] P3 Ep 18/50 | Train: 0.080770 | Val: 0.160676 | LR: 7.42e-06
245
- [02:53:02] P3 Ep 19/50 | Train: 0.080645 | Val: 0.160781 | LR: 7.16e-06
246
- [02:53:46] P3 Ep 20/50 | Train: 0.080037 | Val: 0.160264 | LR: 6.89e-06
247
- [02:54:32] P3 Ep 21/50 | Train: 0.079980 | Val: 0.161155 | LR: 6.62e-06
248
- [02:55:18] P3 Ep 22/50 | Train: 0.079747 | Val: 0.161131 | LR: 6.34e-06
249
- [02:56:01] P3 Ep 23/50 | Train: 0.079374 | Val: 0.161239 | LR: 6.06e-06
250
- [02:56:42] P3 Ep 24/50 | Train: 0.078940 | Val: 0.161157 | LR: 5.78e-06
251
- [02:57:27] P3 Ep 25/50 | Train: 0.078968 | Val: 0.161365 | LR: 5.50e-06
252
- [02:58:13] P3 Ep 26/50 | Train: 0.078512 | Val: 0.161663 | LR: 5.22e-06
253
- [02:58:58] P3 Ep 27/50 | Train: 0.078491 | Val: 0.161840 | LR: 4.94e-06
254
- [02:59:43] P3 Ep 28/50 | Train: 0.078196 | Val: 0.162041 | LR: 4.66e-06
255
- [03:00:28] P3 Ep 29/50 | Train: 0.077853 | Val: 0.162280 | LR: 4.38e-06
256
- [03:01:14] P3 Ep 30/50 | Train: 0.078080 | Val: 0.162482 | LR: 4.11e-06
257
- [03:02:00] P3 Ep 31/50 | Train: 0.077797 | Val: 0.162570 | LR: 3.84e-06
258
- [03:02:45] P3 Ep 32/50 | Train: 0.077377 | Val: 0.162619 | LR: 3.58e-06
259
- [03:03:30] P3 Ep 33/50 | Train: 0.077283 | Val: 0.163112 | LR: 3.33e-06
260
- [03:04:16] P3 Ep 34/50 | Train: 0.077065 | Val: 0.162946 | LR: 3.09e-06
261
- [03:05:01] P3 Ep 35/50 | Train: 0.077059 | Val: 0.162907 | LR: 2.85e-06
262
- [03:05:47] P3 Ep 36/50 | Train: 0.076751 | Val: 0.162916 | LR: 2.63e-06
263
- [03:06:34] P3 Ep 37/50 | Train: 0.076734 | Val: 0.162747 | LR: 2.42e-06
264
- [03:07:19] P3 Ep 38/50 | Train: 0.076768 | Val: 0.163021 | LR: 2.22e-06
265
- [03:08:04] P3 Ep 39/50 | Train: 0.076613 | Val: 0.162848 | LR: 2.03e-06
266
- [03:08:49] P3 Ep 40/50 | Train: 0.076496 | Val: 0.163074 | LR: 1.86e-06
267
- [03:09:34] P3 Ep 41/50 | Train: 0.076267 | Val: 0.163270 | LR: 1.70e-06
268
- [03:10:18] P3 Ep 42/50 | Train: 0.076485 | Val: 0.163313 | LR: 1.56e-06
269
- [03:11:05] P3 Ep 43/50 | Train: 0.076129 | Val: 0.163309 | LR: 1.43e-06
270
- [03:11:50] P3 Ep 44/50 | Train: 0.076036 | Val: 0.163479 | LR: 1.32e-06
271
- [03:12:35] P3 Ep 45/50 | Train: 0.076064 | Val: 0.163314 | LR: 1.22e-06
272
- [03:13:22] P3 Ep 46/50 | Train: 0.076116 | Val: 0.163564 | LR: 1.14e-06
273
- [03:14:08] P3 Ep 47/50 | Train: 0.075992 | Val: 0.163542 | LR: 1.08e-06
274
- [03:14:53] P3 Ep 48/50 | Train: 0.075949 | Val: 0.163568 | LR: 1.04e-06
275
- [03:15:38] P3 Ep 49/50 | Train: 0.075827 | Val: 0.163623 | LR: 1.01e-06
276
- [03:16:24] P3 Ep 50/50 | Train: 0.075700 | Val: 0.163677 | LR: 1.00e-06
277
- [03:16:24] Training complete.
 
1
+ [03:26:21] === Stage A: Generating error patterns ===
2
+ [03:26:26] Generating errors from 5549 windows...
3
+ [03:26:27] Batch 0/347
4
+ [03:26:29] Batch 50/347
5
+ [03:26:30] Batch 100/347
6
+ [03:26:32] Step 1: 2000 errors, mean abs = 0.0122
7
+ [03:26:32] Step 2: 2000 errors, mean abs = 0.0174
8
+ [03:26:32] Step 3: 2000 errors, mean abs = 0.0216
9
+ [03:26:32] Step 4: 2000 errors, mean abs = 0.0257
10
+ [03:26:32] Step 5: 2000 errors, mean abs = 0.0296
11
+ [03:26:32] Step 6: 2000 errors, mean abs = 0.0332
12
+ [03:26:32] Step 7: 2000 errors, mean abs = 0.0366
13
+ [03:26:32] Step 8: 2000 errors, mean abs = 0.0396
14
+ [03:26:32] Error pattern generation complete.
15
+ [03:26:33] Model: FlowWarpAttnUNet (noise-robust), 7,596,742 params
16
+ [03:26:33] === Phase 1: Noise-robust single-step (60 epochs) ===
17
+ [03:26:39] Train: 44392, Val: 5456
18
+ [03:27:17] P1 Ep 1/60 | Train: 0.040061 | Val: 0.049119 | LR: 5.00e-05
19
+ [03:27:17] -> Saved (val=0.049119)
20
+ [03:28:06] P1 Ep 2/60 | Train: 0.037516 | Val: 0.049525 | LR: 4.99e-05
21
+ [03:28:52] P1 Ep 3/60 | Train: 0.036341 | Val: 0.049153 | LR: 4.97e-05
22
+ [03:29:41] P1 Ep 4/60 | Train: 0.036088 | Val: 0.049200 | LR: 4.95e-05
23
+ [03:30:31] P1 Ep 5/60 | Train: 0.035151 | Val: 0.049314 | LR: 4.92e-05
24
+ [03:31:24] P1 Ep 6/60 | Train: 0.035114 | Val: 0.049570 | LR: 4.88e-05
25
+ [03:32:15] P1 Ep 7/60 | Train: 0.034924 | Val: 0.049426 | LR: 4.84e-05
26
+ [03:33:04] P1 Ep 8/60 | Train: 0.034503 | Val: 0.049487 | LR: 4.79e-05
27
+ [03:33:56] P1 Ep 9/60 | Train: 0.034355 | Val: 0.049555 | LR: 4.73e-05
28
+ [03:34:44] P1 Ep 10/60 | Train: 0.034125 | Val: 0.049513 | LR: 4.67e-05
29
+ [03:35:37] P1 Ep 11/60 | Train: 0.033730 | Val: 0.049443 | LR: 4.60e-05
30
+ [03:36:26] P1 Ep 12/60 | Train: 0.033923 | Val: 0.049576 | LR: 4.53e-05
31
+ [03:37:18] P1 Ep 13/60 | Train: 0.033693 | Val: 0.049341 | LR: 4.45e-05
32
+ [03:37:58] P1 Ep 14/60 | Train: 0.033454 | Val: 0.049539 | LR: 4.37e-05
33
+ [03:38:53] P1 Ep 15/60 | Train: 0.033297 | Val: 0.049809 | LR: 4.28e-05
34
+ [03:39:26] P1 Ep 16/60 | Train: 0.033118 | Val: 0.049787 | LR: 4.19e-05
35
+ [03:40:09] P1 Ep 17/60 | Train: 0.032908 | Val: 0.049577 | LR: 4.09e-05
36
+ [03:40:54] P1 Ep 18/60 | Train: 0.032812 | Val: 0.050074 | LR: 3.99e-05
37
+ [03:41:39] P1 Ep 19/60 | Train: 0.032675 | Val: 0.049695 | LR: 3.88e-05
38
+ [03:42:16] P1 Ep 20/60 | Train: 0.032807 | Val: 0.050549 | LR: 3.77e-05
39
+ [03:43:08] P1 Ep 21/60 | Train: 0.032555 | Val: 0.049404 | LR: 3.66e-05
40
+ [03:44:41] P1 Ep 22/60 | Train: 0.032342 | Val: 0.049705 | LR: 3.55e-05
41
+ [03:45:59] P1 Ep 23/60 | Train: 0.032366 | Val: 0.049811 | LR: 3.43e-05
42
+ [03:46:48] P1 Ep 24/60 | Train: 0.032284 | Val: 0.049759 | LR: 3.31e-05
43
+ [03:47:28] P1 Ep 25/60 | Train: 0.032099 | Val: 0.049545 | LR: 3.18e-05
44
+ [03:48:20] P1 Ep 26/60 | Train: 0.032023 | Val: 0.049769 | LR: 3.06e-05
45
+ [03:49:05] P1 Ep 27/60 | Train: 0.031781 | Val: 0.049771 | LR: 2.93e-05
46
+ [03:49:54] P1 Ep 28/60 | Train: 0.031845 | Val: 0.049695 | LR: 2.81e-05
47
+ [03:50:35] P1 Ep 29/60 | Train: 0.031663 | Val: 0.049403 | LR: 2.68e-05
48
+ [03:51:17] P1 Ep 30/60 | Train: 0.031739 | Val: 0.049623 | LR: 2.55e-05
49
+ [03:51:49] P1 Ep 31/60 | Train: 0.031497 | Val: 0.049751 | LR: 2.42e-05
50
+ [03:52:16] P1 Ep 32/60 | Train: 0.031463 | Val: 0.049781 | LR: 2.29e-05
51
+ [03:52:51] P1 Ep 33/60 | Train: 0.031455 | Val: 0.049913 | LR: 2.17e-05
52
+ [03:53:36] P1 Ep 34/60 | Train: 0.031304 | Val: 0.049687 | LR: 2.04e-05
53
+ [03:54:29] P1 Ep 35/60 | Train: 0.031141 | Val: 0.049843 | LR: 1.92e-05
54
+ [03:55:17] P1 Ep 36/60 | Train: 0.031193 | Val: 0.049910 | LR: 1.79e-05
55
+ [03:56:07] P1 Ep 37/60 | Train: 0.031215 | Val: 0.049907 | LR: 1.67e-05
56
+ [03:56:59] P1 Ep 38/60 | Train: 0.030912 | Val: 0.049839 | LR: 1.55e-05
57
+ [03:57:41] P1 Ep 39/60 | Train: 0.031324 | Val: 0.049870 | LR: 1.44e-05
58
+ [03:58:25] P1 Ep 40/60 | Train: 0.031007 | Val: 0.049823 | LR: 1.33e-05
59
+ [03:59:02] P1 Ep 41/60 | Train: 0.030900 | Val: 0.049920 | LR: 1.22e-05
60
+ [03:59:29] P1 Ep 42/60 | Train: 0.030815 | Val: 0.049812 | LR: 1.11e-05
61
+ [04:00:14] P1 Ep 43/60 | Train: 0.030704 | Val: 0.049854 | LR: 1.01e-05
62
+ [04:01:04] P1 Ep 44/60 | Train: 0.030870 | Val: 0.049858 | LR: 9.11e-06
63
+ [04:01:51] P1 Ep 45/60 | Train: 0.030720 | Val: 0.049741 | LR: 8.18e-06
64
+ [04:02:41] P1 Ep 46/60 | Train: 0.030654 | Val: 0.049915 | LR: 7.29e-06
65
+ [04:03:34] P1 Ep 47/60 | Train: 0.030494 | Val: 0.049572 | LR: 6.46e-06
66
+ [04:04:20] P1 Ep 48/60 | Train: 0.030535 | Val: 0.049700 | LR: 5.68e-06
67
+ [04:05:03] P1 Ep 49/60 | Train: 0.030629 | Val: 0.049698 | LR: 4.95e-06
68
+ [04:05:54] P1 Ep 50/60 | Train: 0.030587 | Val: 0.049645 | LR: 4.28e-06
69
+ [04:06:40] P1 Ep 51/60 | Train: 0.030537 | Val: 0.049724 | LR: 3.67e-06
70
+ [04:07:27] P1 Ep 52/60 | Train: 0.030372 | Val: 0.049661 | LR: 3.12e-06
71
+ [04:08:17] P1 Ep 53/60 | Train: 0.030349 | Val: 0.049677 | LR: 2.63e-06
72
+ [04:09:08] P1 Ep 54/60 | Train: 0.030320 | Val: 0.049728 | LR: 2.20e-06
73
+ [04:09:54] P1 Ep 55/60 | Train: 0.030386 | Val: 0.049682 | LR: 1.83e-06
74
+ [04:10:40] P1 Ep 56/60 | Train: 0.030347 | Val: 0.049745 | LR: 1.54e-06
75
+ [04:11:20] P1 Ep 57/60 | Train: 0.030301 | Val: 0.049697 | LR: 1.30e-06
76
+ [04:12:10] P1 Ep 58/60 | Train: 0.030466 | Val: 0.049673 | LR: 1.13e-06
77
+ [04:12:47] P1 Ep 59/60 | Train: 0.030362 | Val: 0.049686 | LR: 1.03e-06
78
+ [04:13:36] P1 Ep 60/60 | Train: 0.030344 | Val: 0.049695 | LR: 1.00e-06
79
+ [04:13:36] === Phase 2: 4-step AR with noise (100 epochs) ===
80
+ [04:13:42] Train: 11098, Val: 1364
81
+ [04:14:56] P2 Ep 1/100 | Train: 0.059848 | Val: 0.104508 | LR: 2.00e-05 | TF: 0.30 | NP: 0.50
82
+ [04:14:56] -> Saved P2 (val=0.104508)
83
+ [04:16:11] P2 Ep 2/100 | Train: 0.059161 | Val: 0.104253 | LR: 2.00e-05 | TF: 0.29 | NP: 0.49
84
+ [04:16:11] -> Saved P2 (val=0.104253)
85
+ [04:17:27] P2 Ep 3/100 | Train: 0.058313 | Val: 0.104213 | LR: 2.00e-05 | TF: 0.29 | NP: 0.49
86
+ [04:17:27] -> Saved P2 (val=0.104213)
87
+ [04:18:43] P2 Ep 4/100 | Train: 0.056654 | Val: 0.104198 | LR: 1.99e-05 | TF: 0.28 | NP: 0.48
88
+ [04:18:43] -> Saved P2 (val=0.104198)
89
+ [04:19:59] P2 Ep 5/100 | Train: 0.057245 | Val: 0.104530 | LR: 1.99e-05 | TF: 0.28 | NP: 0.48
90
+ [04:21:14] P2 Ep 6/100 | Train: 0.056061 | Val: 0.104707 | LR: 1.98e-05 | TF: 0.27 | NP: 0.47
91
+ [04:22:29] P2 Ep 7/100 | Train: 0.056693 | Val: 0.104456 | LR: 1.98e-05 | TF: 0.26 | NP: 0.47
92
+ [04:23:45] P2 Ep 8/100 | Train: 0.056826 | Val: 0.104200 | LR: 1.97e-05 | TF: 0.26 | NP: 0.46
93
+ [04:25:01] P2 Ep 9/100 | Train: 0.055862 | Val: 0.104176 | LR: 1.96e-05 | TF: 0.25 | NP: 0.46
94
+ [04:25:01] -> Saved P2 (val=0.104176)
95
+ [04:26:15] P2 Ep 10/100 | Train: 0.055155 | Val: 0.103997 | LR: 1.95e-05 | TF: 0.25 | NP: 0.46
96
+ [04:26:15] -> Saved P2 (val=0.103997)
97
+ [04:27:31] P2 Ep 11/100 | Train: 0.055672 | Val: 0.103857 | LR: 1.94e-05 | TF: 0.24 | NP: 0.45
98
+ [04:27:31] -> Saved P2 (val=0.103857)
99
+ [04:28:44] P2 Ep 12/100 | Train: 0.055593 | Val: 0.104285 | LR: 1.93e-05 | TF: 0.23 | NP: 0.45
100
+ [04:29:56] P2 Ep 13/100 | Train: 0.054616 | Val: 0.104645 | LR: 1.92e-05 | TF: 0.23 | NP: 0.44
101
+ [04:31:09] P2 Ep 14/100 | Train: 0.055032 | Val: 0.104337 | LR: 1.91e-05 | TF: 0.22 | NP: 0.43
102
+ [04:32:23] P2 Ep 15/100 | Train: 0.054906 | Val: 0.104176 | LR: 1.90e-05 | TF: 0.22 | NP: 0.43
103
+ [04:33:36] P2 Ep 16/100 | Train: 0.053893 | Val: 0.104343 | LR: 1.88e-05 | TF: 0.21 | NP: 0.42
104
+ [04:34:47] P2 Ep 17/100 | Train: 0.054189 | Val: 0.104551 | LR: 1.87e-05 | TF: 0.20 | NP: 0.42
105
+ [04:35:58] P2 Ep 18/100 | Train: 0.054472 | Val: 0.105617 | LR: 1.85e-05 | TF: 0.20 | NP: 0.41
106
+ [04:37:10] P2 Ep 19/100 | Train: 0.054137 | Val: 0.104829 | LR: 1.84e-05 | TF: 0.19 | NP: 0.41
107
+ [04:38:22] P2 Ep 20/100 | Train: 0.054050 | Val: 0.104997 | LR: 1.82e-05 | TF: 0.19 | NP: 0.41
108
+ [04:39:33] P2 Ep 21/100 | Train: 0.054664 | Val: 0.105146 | LR: 1.80e-05 | TF: 0.18 | NP: 0.40
109
+ [04:40:43] P2 Ep 22/100 | Train: 0.053990 | Val: 0.105238 | LR: 1.78e-05 | TF: 0.17 | NP: 0.40
110
+ [04:41:54] P2 Ep 23/100 | Train: 0.053696 | Val: 0.104804 | LR: 1.76e-05 | TF: 0.17 | NP: 0.39
111
+ [04:43:05] P2 Ep 24/100 | Train: 0.053664 | Val: 0.104455 | LR: 1.74e-05 | TF: 0.16 | NP: 0.39
112
+ [04:44:16] P2 Ep 25/100 | Train: 0.053457 | Val: 0.104193 | LR: 1.72e-05 | TF: 0.16 | NP: 0.38
113
+ [04:45:28] P2 Ep 26/100 | Train: 0.053921 | Val: 0.104713 | LR: 1.70e-05 | TF: 0.15 | NP: 0.38
114
+ [04:46:38] P2 Ep 27/100 | Train: 0.053605 | Val: 0.104017 | LR: 1.68e-05 | TF: 0.14 | NP: 0.37
115
+ [04:47:49] P2 Ep 28/100 | Train: 0.054031 | Val: 0.105117 | LR: 1.66e-05 | TF: 0.14 | NP: 0.36
116
+ [04:48:58] P2 Ep 29/100 | Train: 0.053436 | Val: 0.105894 | LR: 1.63e-05 | TF: 0.13 | NP: 0.36
117
+ [04:50:08] P2 Ep 30/100 | Train: 0.053417 | Val: 0.104878 | LR: 1.61e-05 | TF: 0.13 | NP: 0.35
118
+ [04:51:15] P2 Ep 31/100 | Train: 0.053384 | Val: 0.104639 | LR: 1.58e-05 | TF: 0.12 | NP: 0.35
119
+ [04:52:23] P2 Ep 32/100 | Train: 0.053350 | Val: 0.105118 | LR: 1.56e-05 | TF: 0.11 | NP: 0.34
120
+ [04:53:29] P2 Ep 33/100 | Train: 0.053197 | Val: 0.105607 | LR: 1.53e-05 | TF: 0.11 | NP: 0.34
121
+ [04:54:38] P2 Ep 34/100 | Train: 0.053307 | Val: 0.104937 | LR: 1.51e-05 | TF: 0.10 | NP: 0.33
122
+ [04:55:46] P2 Ep 35/100 | Train: 0.054050 | Val: 0.105991 | LR: 1.48e-05 | TF: 0.10 | NP: 0.33
123
+ [04:56:55] P2 Ep 36/100 | Train: 0.053977 | Val: 0.106269 | LR: 1.45e-05 | TF: 0.09 | NP: 0.33
124
+ [04:59:08] P2 Ep 37/100 | Train: 0.053503 | Val: 0.105986 | LR: 1.43e-05 | TF: 0.08 | NP: 0.32
125
+ [05:02:10] P2 Ep 38/100 | Train: 0.053943 | Val: 0.106251 | LR: 1.40e-05 | TF: 0.08 | NP: 0.32
126
+ [05:05:49] P2 Ep 39/100 | Train: 0.053408 | Val: 0.105320 | LR: 1.37e-05 | TF: 0.07 | NP: 0.31
127
+ [05:09:04] P2 Ep 40/100 | Train: 0.053180 | Val: 0.105866 | LR: 1.34e-05 | TF: 0.07 | NP: 0.30
128
+ [05:10:40] P2 Ep 41/100 | Train: 0.053370 | Val: 0.106499 | LR: 1.32e-05 | TF: 0.06 | NP: 0.30
129
+ [05:11:44] P2 Ep 42/100 | Train: 0.053063 | Val: 0.106293 | LR: 1.29e-05 | TF: 0.05 | NP: 0.30
130
+ [05:12:48] P2 Ep 43/100 | Train: 0.053503 | Val: 0.106435 | LR: 1.26e-05 | TF: 0.05 | NP: 0.29
131
+ [05:13:52] P2 Ep 44/100 | Train: 0.053003 | Val: 0.106367 | LR: 1.23e-05 | TF: 0.04 | NP: 0.29
132
+ [05:14:55] P2 Ep 45/100 | Train: 0.053568 | Val: 0.107181 | LR: 1.20e-05 | TF: 0.04 | NP: 0.28
133
+ [05:15:56] P2 Ep 46/100 | Train: 0.052625 | Val: 0.105795 | LR: 1.17e-05 | TF: 0.03 | NP: 0.28
134
+ [05:17:00] P2 Ep 47/100 | Train: 0.053292 | Val: 0.107126 | LR: 1.14e-05 | TF: 0.02 | NP: 0.27
135
+ [05:18:01] P2 Ep 48/100 | Train: 0.053207 | Val: 0.106755 | LR: 1.11e-05 | TF: 0.02 | NP: 0.27
136
+ [05:19:02] P2 Ep 49/100 | Train: 0.053234 | Val: 0.106122 | LR: 1.08e-05 | TF: 0.01 | NP: 0.26
137
+ [05:20:02] P2 Ep 50/100 | Train: 0.052936 | Val: 0.106251 | LR: 1.05e-05 | TF: 0.01 | NP: 0.26
138
+ [05:21:02] P2 Ep 51/100 | Train: 0.053316 | Val: 0.107291 | LR: 1.02e-05 | TF: 0.00 | NP: 0.25
139
+ [05:22:02] P2 Ep 52/100 | Train: 0.052973 | Val: 0.106584 | LR: 9.90e-06 | TF: 0.00 | NP: 0.24
140
+ [05:23:02] P2 Ep 53/100 | Train: 0.052803 | Val: 0.106842 | LR: 9.61e-06 | TF: 0.00 | NP: 0.24
141
+ [05:24:00] P2 Ep 54/100 | Train: 0.052537 | Val: 0.106596 | LR: 9.31e-06 | TF: 0.00 | NP: 0.23
142
+ [05:24:58] P2 Ep 55/100 | Train: 0.052600 | Val: 0.107374 | LR: 9.01e-06 | TF: 0.00 | NP: 0.23
143
+ [05:25:55] P2 Ep 56/100 | Train: 0.052458 | Val: 0.106842 | LR: 8.72e-06 | TF: 0.00 | NP: 0.22
144
+ [05:26:52] P2 Ep 57/100 | Train: 0.052164 | Val: 0.107123 | LR: 8.43e-06 | TF: 0.00 | NP: 0.22
145
+ [05:27:48] P2 Ep 58/100 | Train: 0.051489 | Val: 0.107040 | LR: 8.14e-06 | TF: 0.00 | NP: 0.22
146
+ [05:28:43] P2 Ep 59/100 | Train: 0.051487 | Val: 0.106878 | LR: 7.85e-06 | TF: 0.00 | NP: 0.21
147
+ [05:29:39] P2 Ep 60/100 | Train: 0.051635 | Val: 0.107078 | LR: 7.56e-06 | TF: 0.00 | NP: 0.21
148
+ [05:30:32] P2 Ep 61/100 | Train: 0.051073 | Val: 0.107115 | LR: 7.28e-06 | TF: 0.00 | NP: 0.20
149
+ [05:31:25] P2 Ep 62/100 | Train: 0.051161 | Val: 0.106957 | LR: 7.00e-06 | TF: 0.00 | NP: 0.20
150
+ [05:32:20] P2 Ep 63/100 | Train: 0.050781 | Val: 0.106953 | LR: 6.73e-06 | TF: 0.00 | NP: 0.19
151
+ [05:33:12] P2 Ep 64/100 | Train: 0.051163 | Val: 0.107233 | LR: 6.46e-06 | TF: 0.00 | NP: 0.18
152
+ [05:34:07] P2 Ep 65/100 | Train: 0.051266 | Val: 0.106915 | LR: 6.19e-06 | TF: 0.00 | NP: 0.18
153
+ [05:34:58] P2 Ep 66/100 | Train: 0.050346 | Val: 0.107079 | LR: 5.92e-06 | TF: 0.00 | NP: 0.17
154
+ [05:35:49] P2 Ep 67/100 | Train: 0.050573 | Val: 0.106928 | LR: 5.66e-06 | TF: 0.00 | NP: 0.17
155
+ [05:36:38] P2 Ep 68/100 | Train: 0.050230 | Val: 0.107061 | LR: 5.41e-06 | TF: 0.00 | NP: 0.16
156
+ [05:37:29] P2 Ep 69/100 | Train: 0.050144 | Val: 0.106734 | LR: 5.16e-06 | TF: 0.00 | NP: 0.16
157
+ [05:38:18] P2 Ep 70/100 | Train: 0.049975 | Val: 0.106990 | LR: 4.92e-06 | TF: 0.00 | NP: 0.16
158
+ [05:39:07] P2 Ep 71/100 | Train: 0.049827 | Val: 0.107172 | LR: 4.68e-06 | TF: 0.00 | NP: 0.15
159
+ [05:39:56] P2 Ep 72/100 | Train: 0.049708 | Val: 0.107208 | LR: 4.44e-06 | TF: 0.00 | NP: 0.15
160
+ [05:40:44] P2 Ep 73/100 | Train: 0.049212 | Val: 0.107194 | LR: 4.22e-06 | TF: 0.00 | NP: 0.14
161
+ [05:41:31] P2 Ep 74/100 | Train: 0.049083 | Val: 0.107122 | LR: 4.00e-06 | TF: 0.00 | NP: 0.14
162
+ [05:42:17] P2 Ep 75/100 | Train: 0.049003 | Val: 0.107318 | LR: 3.78e-06 | TF: 0.00 | NP: 0.13
163
+ [05:43:04] P2 Ep 76/100 | Train: 0.049255 | Val: 0.107366 | LR: 3.57e-06 | TF: 0.00 | NP: 0.12
164
+ [05:43:48] P2 Ep 77/100 | Train: 0.048823 | Val: 0.107382 | LR: 3.37e-06 | TF: 0.00 | NP: 0.12
165
+ [05:44:32] P2 Ep 78/100 | Train: 0.048642 | Val: 0.107426 | LR: 3.18e-06 | TF: 0.00 | NP: 0.11
166
+ [05:45:16] P2 Ep 79/100 | Train: 0.048526 | Val: 0.107454 | LR: 2.99e-06 | TF: 0.00 | NP: 0.11
167
+ [05:46:00] P2 Ep 80/100 | Train: 0.048597 | Val: 0.107353 | LR: 2.81e-06 | TF: 0.00 | NP: 0.10
168
+ [05:46:43] P2 Ep 81/100 | Train: 0.048074 | Val: 0.107502 | LR: 2.64e-06 | TF: 0.00 | NP: 0.10
169
+ [05:47:26] P2 Ep 82/100 | Train: 0.048259 | Val: 0.107555 | LR: 2.48e-06 | TF: 0.00 | NP: 0.09
170
+ [05:48:08] P2 Ep 83/100 | Train: 0.048096 | Val: 0.107519 | LR: 2.32e-06 | TF: 0.00 | NP: 0.09
171
+ [05:48:50] P2 Ep 84/100 | Train: 0.048323 | Val: 0.107447 | LR: 2.18e-06 | TF: 0.00 | NP: 0.09
172
+ [05:49:31] P2 Ep 85/100 | Train: 0.047726 | Val: 0.107697 | LR: 2.04e-06 | TF: 0.00 | NP: 0.08
173
+ [05:50:12] P2 Ep 86/100 | Train: 0.047986 | Val: 0.107548 | LR: 1.90e-06 | TF: 0.00 | NP: 0.08
174
+ [05:50:54] P2 Ep 87/100 | Train: 0.047461 | Val: 0.107560 | LR: 1.78e-06 | TF: 0.00 | NP: 0.07
175
+ [05:51:34] P2 Ep 88/100 | Train: 0.047301 | Val: 0.107714 | LR: 1.67e-06 | TF: 0.00 | NP: 0.07
176
+ [05:52:15] P2 Ep 89/100 | Train: 0.047166 | Val: 0.107673 | LR: 1.56e-06 | TF: 0.00 | NP: 0.06
177
+ [05:52:55] P2 Ep 90/100 | Train: 0.047004 | Val: 0.107610 | LR: 1.46e-06 | TF: 0.00 | NP: 0.05
178
+ [05:53:34] P2 Ep 91/100 | Train: 0.047082 | Val: 0.107575 | LR: 1.38e-06 | TF: 0.00 | NP: 0.05
179
+ [05:54:13] P2 Ep 92/100 | Train: 0.046770 | Val: 0.107505 | LR: 1.30e-06 | TF: 0.00 | NP: 0.04
180
+ [05:54:53] P2 Ep 93/100 | Train: 0.046690 | Val: 0.107576 | LR: 1.23e-06 | TF: 0.00 | NP: 0.04
181
+ [05:55:33] P2 Ep 94/100 | Train: 0.046506 | Val: 0.107711 | LR: 1.17e-06 | TF: 0.00 | NP: 0.03
182
+ [05:56:14] P2 Ep 95/100 | Train: 0.046661 | Val: 0.107613 | LR: 1.12e-06 | TF: 0.00 | NP: 0.03
183
+ [05:56:54] P2 Ep 96/100 | Train: 0.046331 | Val: 0.107716 | LR: 1.07e-06 | TF: 0.00 | NP: 0.03
184
+ [05:57:34] P2 Ep 97/100 | Train: 0.046376 | Val: 0.107644 | LR: 1.04e-06 | TF: 0.00 | NP: 0.02
185
+ [05:58:16] P2 Ep 98/100 | Train: 0.046168 | Val: 0.107647 | LR: 1.02e-06 | TF: 0.00 | NP: 0.02
186
+ [05:58:55] P2 Ep 99/100 | Train: 0.046078 | Val: 0.107726 | LR: 1.00e-06 | TF: 0.00 | NP: 0.01
187
+ [05:59:34] P2 Ep 100/100 | Train: 0.045867 | Val: 0.107754 | LR: 1.00e-06 | TF: 0.00 | NP: 0.01
188
+ [05:59:34] === Phase 3: 8-step AR clean (80 epochs) ===
189
+ [05:59:40] Train: 5549, Val: 682
190
+ [06:00:44] P3 Ep 1/80 | Train: 0.091431 | Val: 0.153260 | LR: 1.00e-05
191
+ [06:00:44] -> Saved P3 (val=0.153260)
192
+ [06:01:50] P3 Ep 2/80 | Train: 0.089555 | Val: 0.152113 | LR: 9.99e-06
193
+ [06:01:50] -> Saved P3 (val=0.152113)
194
+ [06:02:58] P3 Ep 3/80 | Train: 0.088352 | Val: 0.151807 | LR: 9.97e-06
195
+ [06:02:58] -> Saved P3 (val=0.151807)
196
+ [06:04:07] P3 Ep 4/80 | Train: 0.087190 | Val: 0.152344 | LR: 9.94e-06
197
+ [06:05:13] P3 Ep 5/80 | Train: 0.086196 | Val: 0.150749 | LR: 9.91e-06
198
+ [06:05:13] -> Saved P3 (val=0.150749)
199
+ [06:06:20] P3 Ep 6/80 | Train: 0.085082 | Val: 0.151936 | LR: 9.88e-06
200
+ [06:07:28] P3 Ep 7/80 | Train: 0.084877 | Val: 0.150434 | LR: 9.83e-06
201
+ [06:07:28] -> Saved P3 (val=0.150434)
202
+ [06:08:35] P3 Ep 8/80 | Train: 0.083996 | Val: 0.151322 | LR: 9.78e-06
203
+ [06:09:42] P3 Ep 9/80 | Train: 0.083521 | Val: 0.151814 | LR: 9.72e-06
204
+ [06:10:49] P3 Ep 10/80 | Train: 0.082798 | Val: 0.151929 | LR: 9.66e-06
205
+ [06:11:57] P3 Ep 11/80 | Train: 0.082589 | Val: 0.151332 | LR: 9.59e-06
206
+ [06:13:04] P3 Ep 12/80 | Train: 0.081946 | Val: 0.152041 | LR: 9.51e-06
207
+ [06:14:12] P3 Ep 13/80 | Train: 0.081198 | Val: 0.152146 | LR: 9.43e-06
208
+ [06:15:19] P3 Ep 14/80 | Train: 0.080969 | Val: 0.152782 | LR: 9.34e-06
209
+ [06:16:26] P3 Ep 15/80 | Train: 0.080584 | Val: 0.152448 | LR: 9.24e-06
210
+ [06:17:34] P3 Ep 16/80 | Train: 0.080236 | Val: 0.152723 | LR: 9.14e-06
211
+ [06:18:41] P3 Ep 17/80 | Train: 0.079582 | Val: 0.153347 | LR: 9.03e-06
212
+ [06:19:48] P3 Ep 18/80 | Train: 0.079417 | Val: 0.153058 | LR: 8.92e-06
213
+ [06:20:55] P3 Ep 19/80 | Train: 0.078599 | Val: 0.153462 | LR: 8.80e-06
214
+ [06:22:02] P3 Ep 20/80 | Train: 0.078601 | Val: 0.154341 | LR: 8.68e-06
215
+ [06:23:10] P3 Ep 21/80 | Train: 0.078163 | Val: 0.154199 | LR: 8.55e-06
216
+ [06:24:15] P3 Ep 22/80 | Train: 0.077885 | Val: 0.154374 | LR: 8.42e-06
217
+ [06:25:26] P3 Ep 23/80 | Train: 0.077421 | Val: 0.154229 | LR: 8.29e-06
218
+ [06:26:34] P3 Ep 24/80 | Train: 0.077010 | Val: 0.154215 | LR: 8.15e-06
219
+ [06:27:44] P3 Ep 25/80 | Train: 0.076748 | Val: 0.155495 | LR: 8.00e-06
220
+ [06:28:59] P3 Ep 26/80 | Train: 0.076498 | Val: 0.155192 | LR: 7.85e-06
221
+ [06:30:07] P3 Ep 27/80 | Train: 0.076752 | Val: 0.154403 | LR: 7.70e-06
222
+ [06:31:14] P3 Ep 28/80 | Train: 0.076078 | Val: 0.155067 | LR: 7.54e-06
223
+ [06:32:22] P3 Ep 29/80 | Train: 0.075813 | Val: 0.155681 | LR: 7.38e-06
224
+ [06:33:30] P3 Ep 30/80 | Train: 0.075561 | Val: 0.155059 | LR: 7.22e-06
225
+ [06:34:39] P3 Ep 31/80 | Train: 0.075418 | Val: 0.155564 | LR: 7.06e-06
226
+ [06:35:46] P3 Ep 32/80 | Train: 0.075340 | Val: 0.155079 | LR: 6.89e-06
227
+ [06:36:54] P3 Ep 33/80 | Train: 0.074928 | Val: 0.155551 | LR: 6.72e-06
228
+ [06:38:01] P3 Ep 34/80 | Train: 0.074463 | Val: 0.155405 | LR: 6.55e-06
229
+ [06:39:09] P3 Ep 35/80 | Train: 0.074743 | Val: 0.155548 | LR: 6.38e-06
230
+ [06:40:17] P3 Ep 36/80 | Train: 0.074348 | Val: 0.155423 | LR: 6.20e-06
231
+ [06:41:29] P3 Ep 37/80 | Train: 0.073928 | Val: 0.155820 | LR: 6.03e-06
232
+ [06:44:39] P3 Ep 38/80 | Train: 0.073954 | Val: 0.155910 | LR: 5.85e-06
233
+ [06:45:46] P3 Ep 39/80 | Train: 0.073907 | Val: 0.156551 | LR: 5.68e-06
234
+ [06:46:53] P3 Ep 40/80 | Train: 0.073698 | Val: 0.156486 | LR: 5.50e-06
235
+ [06:48:00] P3 Ep 41/80 | Train: 0.073378 | Val: 0.156485 | LR: 5.32e-06
236
+ [06:49:08] P3 Ep 42/80 | Train: 0.073260 | Val: 0.155913 | LR: 5.15e-06
237
+ [06:50:15] P3 Ep 43/80 | Train: 0.073193 | Val: 0.156731 | LR: 4.97e-06
238
+ [06:51:22] P3 Ep 44/80 | Train: 0.072849 | Val: 0.156838 | LR: 4.80e-06
239
+ [06:52:30] P3 Ep 45/80 | Train: 0.072790 | Val: 0.156631 | LR: 4.62e-06
240
+ [06:53:37] P3 Ep 46/80 | Train: 0.072858 | Val: 0.157568 | LR: 4.45e-06
241
+ [06:54:45] P3 Ep 47/80 | Train: 0.072551 | Val: 0.156885 | LR: 4.28e-06
242
+ [06:55:52] P3 Ep 48/80 | Train: 0.072227 | Val: 0.156980 | LR: 4.11e-06
243
+ [06:57:02] P3 Ep 49/80 | Train: 0.072218 | Val: 0.157030 | LR: 3.94e-06
244
+ [06:58:11] P3 Ep 50/80 | Train: 0.072351 | Val: 0.156959 | LR: 3.78e-06
245
+ [06:59:18] P3 Ep 51/80 | Train: 0.071689 | Val: 0.157343 | LR: 3.62e-06
246
+ [07:00:25] P3 Ep 52/80 | Train: 0.071861 | Val: 0.157363 | LR: 3.46e-06
247
+ [07:01:33] P3 Ep 53/80 | Train: 0.071651 | Val: 0.158089 | LR: 3.30e-06
248
+ [07:02:41] P3 Ep 54/80 | Train: 0.071780 | Val: 0.157468 | LR: 3.15e-06
249
+ [07:03:48] P3 Ep 55/80 | Train: 0.071592 | Val: 0.158214 | LR: 3.00e-06
250
+ [07:04:56] P3 Ep 56/80 | Train: 0.071415 | Val: 0.157725 | LR: 2.85e-06
251
+ [07:06:03] P3 Ep 57/80 | Train: 0.071473 | Val: 0.157757 | LR: 2.71e-06
252
+ [07:07:11] P3 Ep 58/80 | Train: 0.071411 | Val: 0.157829 | LR: 2.58e-06
253
+ [07:08:18] P3 Ep 59/80 | Train: 0.070987 | Val: 0.158641 | LR: 2.45e-06
254
+ [07:09:25] P3 Ep 60/80 | Train: 0.071145 | Val: 0.158136 | LR: 2.32e-06
255
+ [07:10:34] P3 Ep 61/80 | Train: 0.071238 | Val: 0.158042 | LR: 2.20e-06
256
+ [07:11:41] P3 Ep 62/80 | Train: 0.071220 | Val: 0.158096 | LR: 2.08e-06
257
+ [07:12:49] P3 Ep 63/80 | Train: 0.070899 | Val: 0.158065 | LR: 1.97e-06
258
+ [07:13:56] P3 Ep 64/80 | Train: 0.071116 | Val: 0.158584 | LR: 1.86e-06
259
+ [07:15:03] P3 Ep 65/80 | Train: 0.070894 | Val: 0.158506 | LR: 1.76e-06
260
+ [07:16:11] P3 Ep 66/80 | Train: 0.071008 | Val: 0.157859 | LR: 1.66e-06
261
+ [07:17:19] P3 Ep 67/80 | Train: 0.070859 | Val: 0.158501 | LR: 1.57e-06
262
+ [07:18:27] P3 Ep 68/80 | Train: 0.070568 | Val: 0.158107 | LR: 1.49e-06
263
+ [07:19:34] P3 Ep 69/80 | Train: 0.070750 | Val: 0.158029 | LR: 1.41e-06
264
+ [07:20:42] P3 Ep 70/80 | Train: 0.070671 | Val: 0.158061 | LR: 1.34e-06
265
+ [07:21:50] P3 Ep 71/80 | Train: 0.070272 | Val: 0.158329 | LR: 1.28e-06
266
+ [07:22:57] P3 Ep 72/80 | Train: 0.070669 | Val: 0.158478 | LR: 1.22e-06
267
+ [07:24:05] P3 Ep 73/80 | Train: 0.070424 | Val: 0.158276 | LR: 1.17e-06
268
+ [07:25:12] P3 Ep 74/80 | Train: 0.070503 | Val: 0.158640 | LR: 1.12e-06
269
+ [07:26:19] P3 Ep 75/80 | Train: 0.070522 | Val: 0.158899 | LR: 1.09e-06
270
+ [07:27:27] P3 Ep 76/80 | Train: 0.070232 | Val: 0.158338 | LR: 1.06e-06
271
+ [07:28:34] P3 Ep 77/80 | Train: 0.070314 | Val: 0.158584 | LR: 1.03e-06
272
+ [07:29:42] P3 Ep 78/80 | Train: 0.070658 | Val: 0.158389 | LR: 1.01e-06
273
+ [07:30:50] P3 Ep 79/80 | Train: 0.070537 | Val: 0.158474 | LR: 1.00e-06
274
+ [07:31:57] P3 Ep 80/80 | Train: 0.070149 | Val: 0.158427 | LR: 1.00e-06
275
+ [07:31:57] Cleaned up error patterns.
276
+ [07:31:57] Training complete.