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output_cppo_risk_deepseek.log
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nohup: ignoring input
/root/FinRL_LLM/train_cppo_llm_risk.py:60: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_sentiment'].fillna(0, inplace=True) #0 is outside scope of sentiment scores (min is 1)
/root/FinRL_LLM/train_cppo_llm_risk.py:62: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_risk'].fillna(3, inplace=True) #neutral risk score is 3
Stock Dimension: 84, State Space: 1009
Warning: Log dir /root/spinningup_pytorch/data/cppo/cppo_s0 already exists! Storing info there anyway.
[32;1mLogging data to /root/spinningup_pytorch/data/cppo/cppo_s0/progress.txt[0m
[36;1mSaving config:
[0m
{
"ac_kwargs": {
"hidden_sizes": [
512,
512
]
},
"actor_critic": "MLPActorCritic",
"alpha": 0.85,
"beta": 3000.0,
"clip_ratio": 0.7,
"cvar_clip_ratio": 0.05,
"delay": 1.0,
"env_fn": "<function <lambda> at 0x7d5ff49f67a0>",
"epochs": 20,
"exp_name": "cppo",
"gamma": 0.995,
"lam": 0.95,
"lam_low_bound": 0.001,
"lam_lr": 0.0005,
"lam_start": 0.01,
"logger": {
"<spinup.utils.logx.EpochLogger object at 0x7d5ff48065f0>": {
"epoch_dict": {},
"exp_name": "cppo",
"first_row": true,
"log_current_row": {},
"log_headers": [],
"output_dir": "/root/spinningup_pytorch/data/cppo/cppo_s0",
"output_file": {
"<_io.TextIOWrapper name='/root/spinningup_pytorch/data/cppo/cppo_s0/progress.txt' mode='w' encoding='UTF-8'>": {
"mode": "w"
}
}
}
},
"logger_kwargs": {
"exp_name": "cppo",
"output_dir": "/root/spinningup_pytorch/data/cppo/cppo_s0"
},
"max_ep_len": 3000,
"nu_delay": 0.75,
"nu_lr": 0.0005,
"nu_start": 0.1,
"pi_lr": 3e-05,
"save_freq": 10,
"seed": 0,
"steps_per_epoch": 20000,
"target_kl": 0.35,
"train_pi_iters": 100,
"train_v_iters": 100,
"vf_lr": 0.0001
}
/root/FinRL_LLM/train_cppo_llm_risk.py:60: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_sentiment'].fillna(0, inplace=True) #0 is outside scope of sentiment scores (min is 1)
/root/FinRL_LLM/train_cppo_llm_risk.py:62: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_risk'].fillna(3, inplace=True) #neutral risk score is 3
Stock Dimension: 84, State Space: 1009
/root/FinRL_LLM/train_cppo_llm_risk.py:60: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_sentiment'].fillna(0, inplace=True) #0 is outside scope of sentiment scores (min is 1)
/root/FinRL_LLM/train_cppo_llm_risk.py:62: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_risk'].fillna(3, inplace=True) #neutral risk score is 3
Stock Dimension: 84, State Space: 1009
/root/FinRL_LLM/train_cppo_llm_risk.py:60: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_sentiment'].fillna(0, inplace=True) #0 is outside scope of sentiment scores (min is 1)
/root/FinRL_LLM/train_cppo_llm_risk.py:62: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.
For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.
train['llm_risk'].fillna(3, inplace=True) #neutral risk score is 3
Stock Dimension: 84, State Space: 1009
[32;1m
Number of parameters: pi: 822952, v: 780289
[0m
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 0
update num: 0
-------------------------------------
bad_trajectory_num: 0
update num: 0
---------------------------------------
| Epoch | 0 |
| AverageEpRet | 190 |
| StdEpRet | 43 |
| MaxEpRet | 258 |
| MinEpRet | 125 |
| EpLen | 1.51e+03 |
| AverageVVals | -0.126 |
| StdVVals | 0.169 |
| MaxVVals | 0.399 |
| MinVVals | -0.642 |
| TotalEnvInteracts | 2e+04 |
| LossPi | 0.222 |
| LossV | 1.13e+03 |
| DeltaLossPi | -0.647 |
| DeltaLossV | -465 |
| Entropy | 0.919 |
-------------------------------------
bad_trajectory_num: 0
update num: 0
| KL | 0.0646 |
| ClipFrac | 0.599 |
| StopIter | 99 |
| Time | 293 |
nu: [72.99893]
lam: 1.5099500000000001
-------------------------------------
nu: [76.302376]
lam: 1.5099500000000001
-------------------------------------
---------------------------------------
-------------------------------------
bad_trajectory_num: 1
update num: 1
nu: [94.12457]
lam: 1.5099500000000001
-------------------------------------
nu: [87.603676]
lam: 1.5099500000000001
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
---------------------------------------
| Epoch | 1 |
| AverageEpRet | 175 |
| StdEpRet | 35.2 |
| MaxEpRet | 234 |
| MinEpRet | 118 |
| EpLen | 1.51e+03 |
| AverageVVals | 14.7 |
| StdVVals | 1.3 |
| MaxVVals | 16.1 |
| MinVVals | 9.4 |
-------------------------------------
bad_trajectory_num: 1369
update num: 1368
nu: [94.98837]
lam: [2.971799]
-------------------------------------
-------------------------------------
bad_trajectory_num: 1487
update num: 1485
nu: [83.9682]
lam: [2.9734507]
-------------------------------------
-------------------------------------
bad_trajectory_num: 2063
update num: 2062
nu: [80.16101]
lam: [2.9628878]
-------------------------------------
| TotalEnvInteracts | 4e+04 |
| LossPi | 0.196 |
| LossV | 611 |
| DeltaLossPi | -0.628 |
| DeltaLossV | -217 |
| Entropy | 0.918 |
| KL | 0.118 |
| ClipFrac | 0.645 |
| StopIter | 99 |
| Time | 556 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1846
update num: 1846
nu: [83.07492]
lam: [2.9661484]
-------------------------------------
day: 1508, episode: 20
begin_total_asset: 1000000.00
end_total_asset: 3637798.47
total_reward: 2637798.47
total_cost: 108707.14
total_trades: 85571
Sharpe: 1.095
=================================
day: 1508, episode: 20
begin_total_asset: 1000000.00
end_total_asset: 2059587.22
total_reward: 1059587.22
total_cost: 65155.63
total_trades: 79486
Sharpe: 0.682
=================================
day: 1508, episode: 20
begin_total_asset: 1000000.00
end_total_asset: 3827731.59
total_reward: 2827731.59
total_cost: 107176.37
total_trades: 81202
Sharpe: 1.135
=================================
day: 1508, episode: 20
begin_total_asset: 1000000.00
end_total_asset: 1903960.87
total_reward: 903960.87
total_cost: 66515.81
total_trades: 79727
Sharpe: 0.565
=================================
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1997
update num: 1997
---------------------------------------
| Epoch | 2 |
| AverageEpRet | 168 |
| StdEpRet | 61 |
| MaxEpRet | 283 |
| MinEpRet | 89.8 |
| EpLen | 1.51e+03 |
| AverageVVals | 14.5 |
| StdVVals | 7.04 |
| MaxVVals | 20.9 |
| MinVVals | -8.36 |
| TotalEnvInteracts | 6e+04 |
| LossPi | 0.181 |
| LossV | 500 |
| DeltaLossPi | -0.623 |
| DeltaLossV | -297 |
| Entropy | 0.917 |
| KL | 0.119 |
| ClipFrac | 0.634 |
| StopIter | 99 |
| Time | 829 |
---------------------------------------
-------------------------------------
-------------------------------------
bad_trajectory_num: 1399
update num: 1398
bad_trajectory_num: 1437
update num: 1436
nu: [95.92853]
lam: [4.4314666]
-------------------------------------
nu: [81.51927]
-------------------------------------
lam: [4.424305]
-------------------------------------
nu: [104.9046]
bad_trajectory_num: 1735
update num: 1735
lam: [4.422807]
-------------------------------------
nu: [73.5791]
lam: [4.424611]
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1790
update num: 1790
-------------------------------------
bad_trajectory_num: 2032
update num: 2032
---------------------------------------
| Epoch | 3 |
| AverageEpRet | 191 |
| StdEpRet | 38.6 |
| MaxEpRet | 291 |
| MinEpRet | 130 |
-------------------------------------
bad_trajectory_num: 1485
update num: 1484
| EpLen | 1.51e+03 |
| AverageVVals | 18.8 |
| StdVVals | 9.74 |
| MaxVVals | 25.9 |
| MinVVals | -20.9 |
nu: [86.84967]
nu: [93.683]
nu: [94.798325]
| TotalEnvInteracts | 8e+04 |
| LossPi | 0.166 |
| LossV | 420 |
| DeltaLossPi | -0.634 |
| DeltaLossV | -280 |
lam: [5.8835025]
-------------------------------------
lam: [5.870355]
-------------------------------------
lam: [5.8835454]
| Entropy | 0.916 |
| KL | 0.196 |
| ClipFrac | 0.674 |
-------------------------------------
| StopIter | 99 |
| Time | 1.11e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1158
update num: 1157
nu: [106.62344]
lam: [5.8878217]
-------------------------------------
day: 1508, episode: 30
begin_total_asset: 1000000.00
end_total_asset: 2736059.62
total_reward: 1736059.62
total_cost: 66619.43
total_trades: 79010
Sharpe: 0.964
=================================
day: 1508, episode: 30
begin_total_asset: 1000000.00
end_total_asset: 2620970.02
total_reward: 1620970.02
total_cost: 64181.75
total_trades: 77454
Sharpe: 0.923
=================================
day: 1508, episode: 30
begin_total_asset: 1000000.00
end_total_asset: 3031807.75
total_reward: 2031807.75
total_cost: 58065.44
total_trades: 78419
Sharpe: 0.942
=================================
day: 1508, episode: 30
begin_total_asset: 1000000.00
end_total_asset: 3353927.49
total_reward: 2353927.49
total_cost: 50118.52
total_trades: 79669
Sharpe: 0.924
=================================
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
-------------------------------------
bad_trajectory_num: 1366
update num: 1364
-------------------------------------
bad_trajectory_num: 1763
update num: 1762
---------------------------------------
| Epoch | 4 |
| AverageEpRet | 210 |
| StdEpRet | 48 |
| MaxEpRet | 292 |
| MinEpRet | 129 |
| EpLen | 1.51e+03 |
| AverageVVals | 18 |
| StdVVals | 16.7 |
bad_trajectory_num: 1500
update num: 1499
nu: [92.18594]
| MaxVVals | 30.3 |
| MinVVals | -29 |
| TotalEnvInteracts | 1e+05 |
nu: [101.76114]
nu: [90.709366]
| LossPi | 0.13 |
| LossV | 482 |
| DeltaLossPi | -0.609 |
| DeltaLossV | -332 |
lam: [7.3235135]
lam: [7.3361034]
-------------------------------------
-------------------------------------
lam: [7.340121]
| Entropy | 0.915 |
-------------------------------------
| KL | 0.276 |
| ClipFrac | 0.694 |
| StopIter | 99 |
| Time | 1.39e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1699
update num: 1699
nu: [102.6588]
lam: [7.33451]
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1565
update num: 1564
---------------------------------------
| Epoch | 5 |
| AverageEpRet | 203 |
| StdEpRet | 83.6 |
| MaxEpRet | 372 |
| MinEpRet | 95.4 |
| EpLen | 1.51e+03 |
| AverageVVals | 23.3 |
| StdVVals | 15.2 |
| MaxVVals | 34.1 |
| MinVVals | -33.3 |
| TotalEnvInteracts | 1.2e+05 |
| LossPi | 0.13 |
| LossV | 538 |
-------------------------------------
bad_trajectory_num: 1215
update num: 1213
-------------------------------------
bad_trajectory_num: 1905
update num: 1904
nu: [86.453606]
nu: [121.46776]
lam: [8.778159]
-------------------------------------
| DeltaLossPi | -0.575 |
| DeltaLossV | -317 |
| Entropy | 0.914 |
| KL | 0.268 |
| ClipFrac | 0.708 |
| StopIter | 99 |
| Time | 1.67e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1677
update num: 1677
nu: [90.35503]
lam: [8.785223]
-------------------------------------
lam: [8.794027]
-------------------------------------
nu: [108.267426]
lam: [8.78318]
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 3390
update num: 3389
-------------------------------------
bad_trajectory_num: 1671
update num: 1670
---------------------------------------
-------------------------------------
bad_trajectory_num: 1233
update num: 1232
nu: [79.82698]
| Epoch | 6 |
| AverageEpRet | 216 |
| StdEpRet | 61.7 |
lam: [10.233294]
nu: [102.99779]
lam: [10.240046]
-------------------------------------
| MaxEpRet | 291 |
| MinEpRet | 76.1 |
| EpLen | 1.51e+03 |
| AverageVVals | 19.2 |
| StdVVals | 19.4 |
| MaxVVals | 37.5 |
| MinVVals | -36.7 |
| TotalEnvInteracts | 1.4e+05 |
| LossPi | 0.132 |
| LossV | 467 |
| DeltaLossPi | -0.608 |
| DeltaLossV | -331 |
| Entropy | 0.913 |
| KL | 0.313 |
| ClipFrac | 0.712 |
| StopIter | 99 |
| Time | 1.95e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1819
update num: 1819
nu: [116.825226]
lam: [10.229047]
-------------------------------------
nu: [108.0134]
lam: [10.234932]
-------------------------------------
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1570
update num: 1568
nu: [131.54964]
lam: [11.680925]
-------------------------------------
-------------------------------------
bad_trajectory_num: 1462
update num: 1462
nu: [127.551605]
lam: [11.688547]
-------------------------------------
---------------------------------------
| Epoch | 7 |
| AverageEpRet | 262 |
| StdEpRet | 72.6 |
| MaxEpRet | 395 |
| MinEpRet | 146 |
| EpLen | 1.51e+03 |
| AverageVVals | 18 |
| StdVVals | 20.6 |
| MaxVVals | 40.7 |
| MinVVals | -38.6 |
| TotalEnvInteracts | 1.6e+05 |
| LossPi | 0.128 |
| LossV | 721 |
| DeltaLossPi | -0.597 |
| DeltaLossV | -513 |
| Entropy | 0.912 |
| KL | 0.344 |
| ClipFrac | 0.68 |
| StopIter | 99 |
| Time | 2.24e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 3051
update num: 3050
nu: [88.22248]
lam: [11.670634]
-------------------------------------
-------------------------------------
bad_trajectory_num: 1124
update num: 1123
nu: [108.70604]
lam: [11.69338]
-------------------------------------
day: 1508, episode: 60
begin_total_asset: 1000000.00
end_total_asset: 5057299.85
total_reward: 4057299.85
total_cost: 66499.68
total_trades: 79099
Sharpe: 1.552
=================================
day: 1508, episode: 60
begin_total_asset: 1000000.00
end_total_asset: 3430843.91
total_reward: 2430843.91
total_cost: 54081.58
total_trades: 78211
Sharpe: 1.230
=================================
day: 1508, episode: 60
begin_total_asset: 1000000.00
end_total_asset: 3202476.33
total_reward: 2202476.33
total_cost: 87357.38
total_trades: 79661
Sharpe: 1.014
=================================
day: 1508, episode: 60
begin_total_asset: 1000000.00
end_total_asset: 3390526.18
total_reward: 2390526.18
total_cost: 78335.32
total_trades: 79917
Sharpe: 1.110
=================================
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1194
update num: 1194
-------------------------------------
bad_trajectory_num: 1408
update num: 1408
---------------------------------------
| Epoch | 8 |
| AverageEpRet | 274 |
| StdEpRet | 70.3 |
| MaxEpRet | 407 |
| MinEpRet | 164 |
| EpLen | 1.51e+03 |
| AverageVVals | 32.8 |
| StdVVals | 16.9 |
| MaxVVals | 45.8 |
| MinVVals | -44 |
| TotalEnvInteracts | 1.8e+05 |
| LossPi | 0.149 |
| LossV | 583 |
| DeltaLossPi | -0.593 |
| DeltaLossV | -427 |
| Entropy | 0.911 |
| KL | 0.239 |
| ClipFrac | 0.672 |
| StopIter | 99 |
| Time | 2.51e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1886
update num: 1886
-------------------------------------
nu: [135.99553]
bad_trajectory_num: 895
update num: 895
lam: [13.124771]
-------------------------------------
nu: [134.83575]
lam: [13.139028]
-------------------------------------
nu: [124.88356]
nu: [130.64874]
lam: [13.11515]
lam: [13.126523]
-------------------------------------
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1822
update num: 1822
---------------------------------------
| Epoch | 9 |
| AverageEpRet | 304 |
| StdEpRet | 71.6 |
| MaxEpRet | 416 |
| MinEpRet | 204 |
-------------------------------------
bad_trajectory_num: 1410
update num: 1410
-------------------------------------
| EpLen | 1.51e+03 |
| AverageVVals | 28.7 |
| StdVVals | 23.5 |
bad_trajectory_num: 2204
update num: 2204
| MaxVVals | 49.8 |
| MinVVals | -48.6 |
nu: [159.86572]
lam: [14.556773]
-------------------------------------
| TotalEnvInteracts | 2e+05 |
| LossPi | 0.124 |
| LossV | 580 |
| DeltaLossPi | -0.608 |
| DeltaLossV | -363 |
| Entropy | 0.91 |
| KL | 0.366 |
| ClipFrac | 0.712 |
| StopIter | 99 |
| Time | 2.79e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 1636
update num: 1636
nu: [126.641815]
lam: [14.564081]
-------------------------------------
nu: [134.24445]
lam: [14.549826]
-------------------------------------
nu: [119.65189]
lam: [14.5716095]
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1060
update num: 1059
-------------------------------------
bad_trajectory_num: 1321
update num: 1321
---------------------------------------
| Epoch | 10 |
| AverageEpRet | 342 |
| StdEpRet | 53.3 |
| MaxEpRet | 420 |
| MinEpRet | 260 |
| EpLen | 1.51e+03 |
| AverageVVals | 40.8 |
| StdVVals | 20.1 |
| MaxVVals | 54.6 |
| MinVVals | -53.2 |
-------------------------------------
| TotalEnvInteracts | 2.2e+05 |
nu: [153.87007]
nu: [169.45187]
bad_trajectory_num: 1636
update num: 1636
| LossPi | 0.164 |
lam: [16.011784]
-------------------------------------
lam: [15.982703]
-------------------------------------
| LossV | 647 |
| DeltaLossPi | -0.611 |
| DeltaLossV | -487 |
| Entropy | 0.909 |
| KL | 0.25 |
| ClipFrac | 0.656 |
| StopIter | 99 |
| Time | 3.23e+03 |
---------------------------------------
nu: [172.87714]
-------------------------------------
bad_trajectory_num: 1123
update num: 1123
nu: [164.05241]
lam: [16.000761]
-------------------------------------
lam: [15.97684]
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
---------------------------------------
| Epoch | 11 |
| AverageEpRet | 320 |
| StdEpRet | 64.6 |
| MaxEpRet | 421 |
| MinEpRet | 212 |
| EpLen | 1.51e+03 |
| AverageVVals | 32.7 |
-------------------------------------
bad_trajectory_num: 2670
update num: 2669
-------------------------------------
bad_trajectory_num: 2087
update num: 2086
| StdVVals | 27.1 |
| MaxVVals | 59.7 |
| MinVVals | -58.5 |
-------------------------------------
bad_trajectory_num: 2777
update num: 2777
nu: [158.13693]
nu: [135.34427]
| TotalEnvInteracts | 2.4e+05 |
| LossPi | 0.123 |
| LossV | 817 |
| DeltaLossPi | -0.558 |
| DeltaLossV | -527 |
lam: [17.434849]
-------------------------------------
| Entropy | 0.908 |
| KL | 0.38 |
nu: [140.64539]
| ClipFrac | 0.666 |
lam: [17.397978]
| StopIter | 99 |
| Time | 3.51e+03 |
---------------------------------------
lam: [17.390402]
-------------------------------------
-------------------------------------
-------------------------------------
bad_trajectory_num: 1866
update num: 1866
nu: [152.92398]
lam: [17.418736]
-------------------------------------
day: 1508, episode: 90
begin_total_asset: 1000000.00
end_total_asset: 4143642.48
total_reward: 3143642.48
total_cost: 53144.45
total_trades: 76434
Sharpe: 1.045
=================================
day: 1508, episode: 90
begin_total_asset: 1000000.00
end_total_asset: 4305762.48
total_reward: 3305762.48
total_cost: 64319.93
total_trades: 76589
Sharpe: 1.333
=================================
day: 1508, episode: 90
begin_total_asset: 1000000.00
end_total_asset: 5218973.31
total_reward: 4218973.31
total_cost: 57463.74
total_trades: 77383
Sharpe: 1.290
=================================
day: 1508, episode: 90
begin_total_asset: 1000000.00
end_total_asset: 5501081.01
total_reward: 4501081.01
total_cost: 42529.42
total_trades: 75970
Sharpe: 1.354
=================================
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
---------------------------------------
| Epoch | 12 |
| AverageEpRet | 358 |
| StdEpRet | 58.3 |
| MaxEpRet | 445 |
| MinEpRet | 243 |
| EpLen | 1.51e+03 |
| AverageVVals | 39.4 |
-------------------------------------
bad_trajectory_num: 1239
update num: 1239
-------------------------------------
bad_trajectory_num: 1847
update num: 1846
-------------------------------------
| StdVVals | 30.5 |
| MaxVVals | 64.6 |
| MinVVals | -64.4 |
| TotalEnvInteracts | 2.6e+05 |
| LossPi | 0.135 |
| LossV | 1.05e+03 |
| DeltaLossPi | -0.547 |
| DeltaLossV | -681 |
bad_trajectory_num: 1382
nu: [168.13005]
nu: [179.41577]
lam: [18.85578]
update num: 1381
-------------------------------------
| Entropy | 0.907 |
| KL | 0.346 |
| ClipFrac | 0.666 |
| StopIter | 99 |
lam: [18.82008]
-------------------------------------
nu: [151.18808]
| Time | 3.79e+03 |
---------------------------------------
lam: [18.830305]
-------------------------------------
bad_trajectory_num: 1508
update num: 1508
-------------------------------------
nu: [166.08765]
lam: [18.842274]
-------------------------------------
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1797
update num: 1796
---------------------------------------
| Epoch | 13 |
| AverageEpRet | 372 |
| StdEpRet | 62.9 |
| MaxEpRet | 465 |
| MinEpRet | 272 |
| EpLen | 1.51e+03 |
| AverageVVals | 35.2 |
| StdVVals | 32.4 |
-------------------------------------
bad_trajectory_num: 1923
update num: 1923
-------------------------------------
bad_trajectory_num: 2182
update num: 2182
nu: [179.87926]
| MaxVVals | 70.1 |
| MinVVals | -70.1 |
| TotalEnvInteracts | 2.8e+05 |
nu: [183.2607]
lam: [20.254711]
-------------------------------------
| LossPi | 0.146 |
nu: [176.33905]
lam: [20.236015]
| LossV | 1.18e+03 |
| DeltaLossPi | -0.532 |
-------------------------------------
lam: [20.266071]
-------------------------------------
| DeltaLossV | -654 |
| Entropy | 0.905 |
| KL | 0.277 |
| ClipFrac | 0.646 |
| StopIter | 99 |
| Time | 4.07e+03 |
---------------------------------------
-------------------------------------
bad_trajectory_num: 2270
update num: 2270
nu: [164.6059]
lam: [20.25923]
-------------------------------------
day: 1508, episode: 100
begin_total_asset: 1000000.00
end_total_asset: 3466612.35
total_reward: 2466612.35
total_cost: 59661.07
total_trades: 79857
Sharpe: 1.075
=================================
day: 1508, episode: 100
begin_total_asset: 1000000.00
end_total_asset: 4994537.53
total_reward: 3994537.53
total_cost: 40163.27
total_trades: 75877
Sharpe: 1.249
=================================
day: 1508, episode: 100
begin_total_asset: 1000000.00
end_total_asset: 3571442.91
total_reward: 2571442.91
total_cost: 55574.63
total_trades: 76621
Sharpe: 1.056
=================================
day: 1508, episode: 100
begin_total_asset: 1000000.00
end_total_asset: 4472589.25
total_reward: 3472589.25
total_cost: 63489.99
total_trades: 81730
Sharpe: 1.381
=================================
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
Warning: trajectory cut off by epoch at 473 steps.
-------------------------------------
bad_trajectory_num: 1903
update num: 1903
---------------------------------------
| Epoch | 14 |
| AverageEpRet | 373 |
| StdEpRet | 85.7 |
| MaxEpRet | 527 |
| MinEpRet | 245 |
| EpLen | 1.51e+03 |
| AverageVVals | 43.6 |
| StdVVals | 35.2 |
| MaxVVals | 77.3 |
| MinVVals | -75.3 |
| TotalEnvInteracts | 3e+05 |