Johnny Fernandes
82 lines
6.0 KiB
Plaintext
82 lines
6.0 KiB
Plaintext
Config loaded from config.json
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Config: {'W_PER_SHEEP': 2.0, 'W_ALIGN': 0.05, 'W_PEN_BONUS': 10.0, 'W_COMPLETE': 100.0, 'W_STEP_COST': 0.02, 'W_SOUTH': 0.01, 'W_COMPACT': 0.0, 'W_WALL_TOUCH': 0.0, 'WALL_TOUCH_BUFFER': 0.4, 'ALIGN_SHAPE': 'standoff', 'ALIGN_GATED': True, 'ENTRY_AWARE': True, 'ent_coef': 0.02}
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Run dir: runs/webots_n3
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Curriculum: 1 → 3 sheep, 1,500,000 steps/stage
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[Stage n_sheep=1] training 1,500,000 steps
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... [1 sheep | 100,000 steps | ret(last 41)=-22.59 win_sr=15% cum_sr=15%]
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... [1 sheep | 200,000 steps | ret(last 50)=-24.68 win_sr=12% cum_sr=13%]
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... [1 sheep | 300,000 steps | ret(last 50)=-23.63 win_sr=10% cum_sr=11%]
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... [1 sheep | 400,000 steps | ret(last 50)=-18.18 win_sr=12% cum_sr=12%]
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... [1 sheep | 500,000 steps | ret(last 50)=+18.15 win_sr=100% cum_sr=37%]
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... [1 sheep | 600,000 steps | ret(last 50)=+14.43 win_sr=100% cum_sr=69%]
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... [1 sheep | 700,000 steps | ret(last 50)=+14.09 win_sr=100% cum_sr=81%]
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... [1 sheep | 800,000 steps | ret(last 50)=+13.60 win_sr=100% cum_sr=87%]
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... [1 sheep | 900,000 steps | ret(last 50)=+13.64 win_sr=100% cum_sr=90%]
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... [1 sheep | 1,000,000 steps | ret(last 50)=+13.70 win_sr=100% cum_sr=92%]
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... [1 sheep | 1,100,000 steps | ret(last 50)=+13.03 win_sr=100% cum_sr=93%]
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... [1 sheep | 1,200,000 steps | ret(last 50)=+13.32 win_sr=100% cum_sr=94%]
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... [1 sheep | 1,300,000 steps | ret(last 50)=+13.19 win_sr=100% cum_sr=95%]
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... [1 sheep | 1,400,000 steps | ret(last 50)=+13.56 win_sr=100% cum_sr=95%]
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... [1 sheep | 1,500,000 steps | ret(last 50)=+13.20 win_sr=100% cum_sr=96%]
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[Stage n_sheep=1] evaluating 30 eps
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[Stage n_sheep=1] sr=80% mean_len=687 mean_min_pen=3.7m mean_act=0.16
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failure modes: SUCCESS=24 COMPACT_CANT_DRIVE=6
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reward/step: progress=+0.0388 alignment=+0.0002 south=-0.0022 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0117 step_cost=-0.0200 complete=+0.1165
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[Stage n_sheep=2] training 1,500,000 steps
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... [2 sheep | 1,507,336 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [2 sheep | 1,607,336 steps | ret(last 41)=-9.02 win_sr=2% cum_sr=2%]
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... [2 sheep | 1,707,336 steps | ret(last 50)=-7.70 win_sr=6% cum_sr=4%]
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... [2 sheep | 1,807,336 steps | ret(last 50)=-5.98 win_sr=16% cum_sr=9%]
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... [2 sheep | 1,907,336 steps | ret(last 50)=-6.55 win_sr=16% cum_sr=10%]
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... [2 sheep | 2,007,336 steps | ret(last 50)=-9.51 win_sr=10% cum_sr=10%]
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... [2 sheep | 2,107,336 steps | ret(last 50)=-0.32 win_sr=36% cum_sr=15%]
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... [2 sheep | 2,207,336 steps | ret(last 50)=+7.58 win_sr=76% cum_sr=28%]
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... [2 sheep | 2,307,336 steps | ret(last 50)=+16.41 win_sr=100% cum_sr=41%]
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... [2 sheep | 2,407,336 steps | ret(last 50)=+17.65 win_sr=100% cum_sr=54%]
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... [2 sheep | 2,507,336 steps | ret(last 50)=+18.87 win_sr=100% cum_sr=63%]
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... [2 sheep | 2,607,336 steps | ret(last 50)=+19.68 win_sr=100% cum_sr=69%]
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... [2 sheep | 2,707,336 steps | ret(last 50)=+19.69 win_sr=100% cum_sr=73%]
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... [2 sheep | 2,807,336 steps | ret(last 50)=+19.71 win_sr=100% cum_sr=77%]
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... [2 sheep | 2,907,336 steps | ret(last 50)=+18.49 win_sr=100% cum_sr=79%]
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... [2 sheep | 3,007,336 steps | ret(last 50)=+19.24 win_sr=100% cum_sr=81%]
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[Stage n_sheep=2] evaluating 30 eps
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[Stage n_sheep=2] sr=100% mean_len=654 mean_min_pen=3.4m mean_act=0.87
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failure modes: SUCCESS=30
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reward/step: progress=+0.0905 alignment=+0.0136 south=-0.0078 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0306 step_cost=-0.0200 complete=+0.1529
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[Stage n_sheep=3] training 1,500,000 steps
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... [3 sheep | 3,014,664 steps | ret(last 0)=+nan win_sr=nan% cum_sr=nan%]
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... [3 sheep | 3,114,664 steps | ret(last 50)=+25.01 win_sr=100% cum_sr=100%]
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... [3 sheep | 3,214,664 steps | ret(last 50)=+23.20 win_sr=98% cum_sr=99%]
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... [3 sheep | 3,314,664 steps | ret(last 50)=+24.99 win_sr=100% cum_sr=100%]
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... [3 sheep | 3,414,664 steps | ret(last 50)=+24.87 win_sr=100% cum_sr=100%]
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... [3 sheep | 3,514,664 steps | ret(last 50)=+24.74 win_sr=100% cum_sr=100%]
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... [3 sheep | 3,614,664 steps | ret(last 50)=+21.31 win_sr=100% cum_sr=100%]
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... [3 sheep | 3,714,664 steps | ret(last 50)=+22.95 win_sr=98% cum_sr=100%]
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... [3 sheep | 3,814,664 steps | ret(last 50)=+23.87 win_sr=100% cum_sr=100%]
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... [3 sheep | 3,914,664 steps | ret(last 50)=+23.55 win_sr=100% cum_sr=100%]
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... [3 sheep | 4,014,664 steps | ret(last 50)=+26.08 win_sr=100% cum_sr=100%]
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... [3 sheep | 4,114,664 steps | ret(last 50)=+24.06 win_sr=100% cum_sr=100%]
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... [3 sheep | 4,214,664 steps | ret(last 50)=+24.43 win_sr=100% cum_sr=100%]
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... [3 sheep | 4,314,664 steps | ret(last 50)=+21.18 win_sr=96% cum_sr=100%]
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... [3 sheep | 4,414,664 steps | ret(last 50)=+23.24 win_sr=100% cum_sr=100%]
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... [3 sheep | 4,514,664 steps | ret(last 50)=+23.97 win_sr=100% cum_sr=100%]
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[Stage n_sheep=3] evaluating 30 eps
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[Stage n_sheep=3] sr=73% mean_len=1270 mean_min_pen=1.8m mean_act=1.12
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failure modes: SUCCESS=22 PARTIAL_1of3=8
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reward/step: progress=+0.0685 alignment=+0.0103 south=-0.0295 compact=+0.0000 wall_touch=+0.0000 pen_bonus=+0.0194 step_cost=-0.0200 complete=+0.0578
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======================================================================
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TRAINING SUMMARY
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======================================================================
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n_sheep=1 sr= 80% len= 687 min_pen= 3.7m act=0.16
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n_sheep=2 sr=100% len= 654 min_pen= 3.4m act=0.87
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n_sheep=3 sr= 73% len= 1270 min_pen= 1.8m act=1.12
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Total time: 23.6 min
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Artefacts: runs/webots_n3/
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Plots: runs/webots_n3/success_rate.png, runs/webots_n3/eval/
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