Best model: CFG_XAG_ASIAN_V6/run_20260601_215137_v6_asian
Browse files
workspaces/CFG_XAG_ASIAN_V6/runs/run_20260601_215137_v6_asian/results/train_v3.log
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[Epoch 4] Loss(MSE:0.1823/CE:0.9767) | LR=1.64e-05 | Val V6 Simulator Score [0.000] - Loss(MSE:0.0159/CE:0.7135) | >=53%: WR=30.0% | Score=0.000 | N=30 (0B/30S Bal:0.00) | >=54%: WR=35.0% | Score=0.063 | N=20 (0B/20S Bal:0.00) | >=55%: WR=33.3% | Score=0.000 | N=9 (0B/9S Bal:0.00) | >=56%: WR=0.0% | Score=0.000 | N=3 (0B/3S Bal:0.00)
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[ARGO2] MO HINH HOI TU TOT NHAT! Val CE Loss = 0.7287 (WR: 35.0%). Luu model...
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[21:52:54] PUSH RUN: run_20260601_215137_v6_asian -> HF (new/changed files only)...
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[Epoch 4] Loss(MSE:0.1823/CE:0.9767) | LR=1.64e-05 | Val V6 Simulator Score [0.000] - Loss(MSE:0.0159/CE:0.7135) | >=53%: WR=30.0% | Score=0.000 | N=30 (0B/30S Bal:0.00) | >=54%: WR=35.0% | Score=0.063 | N=20 (0B/20S Bal:0.00) | >=55%: WR=33.3% | Score=0.000 | N=9 (0B/9S Bal:0.00) | >=56%: WR=0.0% | Score=0.000 | N=3 (0B/3S Bal:0.00)
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[ARGO2] MO HINH HOI TU TOT NHAT! Val CE Loss = 0.7287 (WR: 35.0%). Luu model...
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[21:52:54] PUSH RUN: run_20260601_215137_v6_asian -> HF (new/changed files only)...
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[21:52:56] ✔️ Push run run_20260601_215137_v6_asian hoàn tất!
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[Epoch 5] Loss(MSE:0.1834/CE:0.9759) | LR=1.52e-05 | Val V6 Simulator Score [0.000] - Loss(MSE:0.0165/CE:0.6975) | >=53%: WR=34.8% | Score=0.189 | N=23 (3B/20S Bal:0.15) | >=54%: WR=0.0% | Score=0.000 | N=4 (0B/4S Bal:0.00) | >=55%: WR=0.0% | Score=0.000 | N=1 (0B/1S Bal:0.00) | >=56%: WR=0.0% | Score=0.000 | N=0 (0B/0S Bal:0.00)
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[ARGO2] MO HINH HOI TU TOT NHAT! Val CE Loss = 0.7131 (WR: 34.8%). Luu model...
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[21:53:09] PUSH RUN: run_20260601_215137_v6_asian -> HF (new/changed files only)...
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workspaces/CFG_XAG_ASIAN_V6/runs/run_20260601_215137_v6_asian/results/training_metrics_v3.json
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"sessions": {
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"asian": {
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"threshold_metrics": [
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"total_signals":
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"win_rate": 0.
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"avg_win_return": 0.001,
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"avg_loss_return": 0.001,
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"ev_score": 0.
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"sharpe_score": 0.0,
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"tus_score": 0.
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"avg_win_return": 0.001,
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"ev_score": 0.
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"avg_loss_return": 0.001,
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"sharpe_score": 0.0,
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