myTestFreqAI/debug.log
zhangkun9038@dingtalk.com cdce4eba5b run.sh
2025-05-01 12:33:24 +08:00

167 KiB
Raw Blame History

2025-04-29 01:22:03,335 - freqtrade - INFO - freqtrade 2025.3
2025-04-29 01:22:03,551 - numexpr.utils - INFO - NumExpr defaulting to 12 threads.
2025-04-29 01:22:04,957 - freqtrade.configuration.load_config - INFO - Using config: /freqtrade/config_examples/config_freqai.okx.json ...
2025-04-29 01:22:04,958 - freqtrade.configuration.load_config - INFO - Using config: /freqtrade/templates/FreqaiExampleStrategy.json ...
2025-04-29 01:22:04,960 - freqtrade.loggers - INFO - Enabling colorized output.
2025-04-29 01:22:04,960 - root - INFO - Logfile configured
2025-04-29 01:22:04,960 - freqtrade.loggers - INFO - Verbosity set to 0
2025-04-29 01:22:04,961 - freqtrade.configuration.configuration - INFO - Using additional Strategy lookup path: /freqtrade/templates
2025-04-29 01:22:04,961 - freqtrade.configuration.configuration - INFO - Using max_open_trades: 4 ...
2025-04-29 01:22:04,961 - freqtrade.configuration.configuration - INFO - Parameter --timerange detected: 20250101-20250420 ...
2025-04-29 01:22:04,998 - freqtrade.configuration.configuration - INFO - Using user-data directory: /freqtrade/user_data ...
2025-04-29 01:22:04,999 - freqtrade.configuration.configuration - INFO - Using data directory: /freqtrade/user_data/data/okx ...
2025-04-29 01:22:05,000 - freqtrade.configuration.configuration - INFO - Parameter --cache=none detected ...
2025-04-29 01:22:05,000 - freqtrade.configuration.configuration - INFO - Filter trades by timerange: 20250101-20250420
2025-04-29 01:22:05,001 - freqtrade.configuration.configuration - INFO - Using freqaimodel class name: XGBoostRegressor
2025-04-29 01:22:05,002 - freqtrade.exchange.check_exchange - INFO - Checking exchange...
2025-04-29 01:22:05,008 - freqtrade.exchange.check_exchange - INFO - Exchange "okx" is officially supported by the Freqtrade development team.
2025-04-29 01:22:05,008 - freqtrade.configuration.configuration - INFO - Using pairlist from configuration.
2025-04-29 01:22:05,009 - freqtrade.configuration.config_validation - INFO - Validating configuration ...
2025-04-29 01:22:05,011 - freqtrade.commands.optimize_commands - INFO - Starting freqtrade in Backtesting mode
2025-04-29 01:22:05,012 - freqtrade.exchange.exchange - INFO - Instance is running with dry_run enabled
2025-04-29 01:22:05,012 - freqtrade.exchange.exchange - INFO - Using CCXT 4.4.69
2025-04-29 01:22:05,012 - freqtrade.exchange.exchange - INFO - Applying additional ccxt config: {'enableRateLimit': True, 'rateLimit': 500, 'options': {'defaultType': 'spot'}}
2025-04-29 01:22:05,017 - freqtrade.exchange.exchange - INFO - Applying additional ccxt config: {'enableRateLimit': True, 'rateLimit': 500, 'options': {'defaultType': 'spot'}, 'timeout': 20000}
2025-04-29 01:22:05,023 - freqtrade.exchange.exchange - INFO - Using Exchange "OKX"
2025-04-29 01:22:07,636 - freqtrade.resolvers.exchange_resolver - INFO - Using resolved exchange 'Okx'...
2025-04-29 01:22:07,657 - freqtrade.resolvers.iresolver - INFO - Using resolved strategy FreqaiExampleStrategy from '/freqtrade/templates/FreqaiExampleStrategy.py'...
2025-04-29 01:22:07,657 - freqtrade.strategy.hyper - INFO - Loading parameters from file /freqtrade/templates/FreqaiExampleStrategy.json
2025-04-29 01:22:07,658 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'timeframe' with value in config file: 3m.
2025-04-29 01:22:07,658 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'stoploss' with value in config file: -0.05.
2025-04-29 01:22:07,659 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'stake_currency' with value in config file: USDT.
2025-04-29 01:22:07,659 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'stake_amount' with value in config file: 150.
2025-04-29 01:22:07,659 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'startup_candle_count' with value in config file: 30.
2025-04-29 01:22:07,660 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'unfilledtimeout' with value in config file: {'entry': 5, 'exit': 15, 'exit_timeout_count': 0, 'unit':
'minutes'}.
2025-04-29 01:22:07,660 - freqtrade.resolvers.strategy_resolver - INFO - Override strategy 'max_open_trades' with value in config file: 4.
2025-04-29 01:22:07,661 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using minimal_roi: {'0': 0.132, '8': 0.047, '14': 0.007, '60': 0}
2025-04-29 01:22:07,661 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using timeframe: 3m
2025-04-29 01:22:07,661 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using stoploss: -0.05
2025-04-29 01:22:07,662 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using trailing_stop: True
2025-04-29 01:22:07,662 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using trailing_stop_positive: 0.01
2025-04-29 01:22:07,662 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using trailing_stop_positive_offset: 0.02
2025-04-29 01:22:07,663 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using trailing_only_offset_is_reached: False
2025-04-29 01:22:07,663 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using use_custom_stoploss: False
2025-04-29 01:22:07,663 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using process_only_new_candles: True
2025-04-29 01:22:07,664 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using order_types: {'entry': 'limit', 'exit': 'limit', 'stoploss': 'limit', 'stoploss_on_exchange': False,
'stoploss_on_exchange_interval': 60}
2025-04-29 01:22:07,664 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using order_time_in_force: {'entry': 'GTC', 'exit': 'GTC'}
2025-04-29 01:22:07,664 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using stake_currency: USDT
2025-04-29 01:22:07,664 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using stake_amount: 150
2025-04-29 01:22:07,665 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using startup_candle_count: 30
2025-04-29 01:22:07,665 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using unfilledtimeout: {'entry': 5, 'exit': 15, 'exit_timeout_count': 0, 'unit': 'minutes'}
2025-04-29 01:22:07,665 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using use_exit_signal: True
2025-04-29 01:22:07,666 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using exit_profit_only: False
2025-04-29 01:22:07,666 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using ignore_roi_if_entry_signal: False
2025-04-29 01:22:07,666 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using exit_profit_offset: 0.0
2025-04-29 01:22:07,666 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using disable_dataframe_checks: False
2025-04-29 01:22:07,667 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using ignore_buying_expired_candle_after: 0
2025-04-29 01:22:07,667 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using position_adjustment_enable: False
2025-04-29 01:22:07,667 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using max_entry_position_adjustment: -1
2025-04-29 01:22:07,667 - freqtrade.resolvers.strategy_resolver - INFO - Strategy using max_open_trades: 4
2025-04-29 01:22:07,668 - freqtrade.configuration.config_validation - INFO - Validating configuration ...
2025-04-29 01:22:07,671 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist StaticPairList from '/freqtrade/freqtrade/plugins/pairlist/StaticPairList.py'...
2025-04-29 01:22:07,677 - freqtrade.optimize.backtesting - INFO - Using fee 0.1500% - worst case fee from exchange (lowest tier).
2025-04-29 01:22:07,678 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 3m to 14450
2025-04-29 01:22:07,678 - freqtrade.data.history.history_utils - INFO - Using indicator startup period: 14450 ...
2025-04-29 01:22:07,842 - freqtrade.optimize.backtesting - INFO - Loading data from 2024-12-01 21:30:00 up to 2025-04-20 00:00:00 (139 days).
2025-04-29 01:22:07,843 - freqtrade.optimize.backtesting - INFO - Dataload complete. Calculating indicators
2025-04-29 01:22:07,843 - freqtrade.optimize.backtesting - INFO - Running backtesting for Strategy FreqaiExampleStrategy
2025-04-29 01:22:09,440 - matplotlib.font_manager - INFO - generated new fontManager
2025-04-29 01:22:09,642 - freqtrade.resolvers.iresolver - INFO - Using resolved freqaimodel XGBoostRegressor from '/freqtrade/freqtrade/freqai/prediction_models/XGBoostRegressor.py'...
2025-04-29 01:22:09,643 - freqtrade.freqai.data_drawer - INFO - Could not find existing datadrawer, starting from scratch
2025-04-29 01:22:09,643 - freqtrade.freqai.data_drawer - INFO - Could not find existing historic_predictions, starting from scratch
2025-04-29 01:22:09,643 - freqtrade.freqai.freqai_interface - INFO - Set fresh train queue from whitelist. Queue: ['BTC/USDT', 'SOL/USDT']
2025-04-29 01:22:09,644 - freqtrade.strategy.hyper - INFO - Strategy Parameter: buy_rsi = 39.92672300850069
2025-04-29 01:22:09,644 - freqtrade.strategy.hyper - INFO - Strategy Parameter: sell_rsi = 69.92672300850067
2025-04-29 01:22:09,645 - freqtrade.strategy.hyper - INFO - No params for protection found, using default values.
2025-04-29 01:22:09,650 - FreqaiExampleStrategy - INFO - 处理交易对BTC/USDT
2025-04-29 01:22:09,652 - freqtrade.freqai.freqai_interface - INFO - Training 11 timeranges
2025-04-29 01:22:09,654 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2024-12-02 00:00:00 to 2025-01-01 00:00:00, 1/11 trains
2025-04-29 01:22:09,654 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1735689600_prediction.feather
2025-04-29 01:22:09,754 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 5m to 8690
2025-04-29 01:22:09,755 - freqtrade.data.dataprovider - INFO - Loading data for BTC/USDT 5m from 2024-12-01 19:50:00 to 2025-04-20 00:00:00
2025-04-29 01:22:09,858 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 1h to 770
2025-04-29 01:22:09,859 - freqtrade.data.dataprovider - INFO - Loading data for BTC/USDT 1h from 2024-11-29 22:00:00 to 2025-04-20 00:00:00
2025-04-29 01:22:09,960 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 3m to 14450
2025-04-29 01:22:09,960 - freqtrade.data.dataprovider - INFO - Loading data for ETH/USDT 3m from 2024-12-01 21:30:00 to 2025-04-20 00:00:00
2025-04-29 01:22:10,084 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 5m to 8690
2025-04-29 01:22:10,084 - freqtrade.data.dataprovider - INFO - Loading data for ETH/USDT 5m from 2024-12-01 19:50:00 to 2025-04-20 00:00:00
2025-04-29 01:22:10,182 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 1h to 770
2025-04-29 01:22:10,182 - freqtrade.data.dataprovider - INFO - Loading data for ETH/USDT 1h from 2024-11-29 22:00:00 to 2025-04-20 00:00:00
2025-04-29 01:22:10,260 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:10,265 - FreqaiExampleStrategy - INFO - 目标列形状:(14450,)
2025-04-29 01:22:10,267 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.152831
1 0.003285 50.152831
2 0.001898 50.152831
3 0.000484 50.152831
4 0.001688 50.152831
2025-04-29 01:22:10,270 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:10,275 - FreqaiExampleStrategy - INFO - 目标列形状:(19250,)
2025-04-29 01:22:10,277 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.202701
1 0.003285 50.202701
2 0.001898 50.202701
3 0.000484 50.202701
4 0.001688 50.202701
2025-04-29 01:22:10,281 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1735689600/cb_btc_1735689600
2025-04-29 01:22:10,281 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:10,297 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:10,298 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2024-12-02 to 2024-12-31 --------------------
2025-04-29 01:22:15,331 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:15,332 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.24624 validation_1-rmse:0.26036
[1] validation_0-rmse:0.24176 validation_1-rmse:0.25460
[2] validation_0-rmse:0.23782 validation_1-rmse:0.24904
[3] validation_0-rmse:0.23408 validation_1-rmse:0.24381
[4] validation_0-rmse:0.23057 validation_1-rmse:0.23882
[5] validation_0-rmse:0.22701 validation_1-rmse:0.23409
[6] validation_0-rmse:0.22400 validation_1-rmse:0.22962
[7] validation_0-rmse:0.22088 validation_1-rmse:0.22533
[8] validation_0-rmse:0.21817 validation_1-rmse:0.22130
[9] validation_0-rmse:0.21491 validation_1-rmse:0.21740
[10] validation_0-rmse:0.21265 validation_1-rmse:0.21347
[11] validation_0-rmse:0.20982 validation_1-rmse:0.20978
[12] validation_0-rmse:0.20747 validation_1-rmse:0.20640
[13] validation_0-rmse:0.20512 validation_1-rmse:0.20299
[14] validation_0-rmse:0.20280 validation_1-rmse:0.19966
[15] validation_0-rmse:0.20012 validation_1-rmse:0.19656
[16] validation_0-rmse:0.19785 validation_1-rmse:0.19346
[17] validation_0-rmse:0.19572 validation_1-rmse:0.19054
[18] validation_0-rmse:0.19400 validation_1-rmse:0.18759
[19] validation_0-rmse:0.19164 validation_1-rmse:0.18488
[20] validation_0-rmse:0.18956 validation_1-rmse:0.18205
[21] validation_0-rmse:0.18746 validation_1-rmse:0.17951
[22] validation_0-rmse:0.18593 validation_1-rmse:0.17696
[23] validation_0-rmse:0.18395 validation_1-rmse:0.17465
[24] validation_0-rmse:0.18249 validation_1-rmse:0.17217
[25] validation_0-rmse:0.18084 validation_1-rmse:0.16993
[26] validation_0-rmse:0.17928 validation_1-rmse:0.16771
[27] validation_0-rmse:0.17776 validation_1-rmse:0.16571
[28] validation_0-rmse:0.17652 validation_1-rmse:0.16356
[29] validation_0-rmse:0.17499 validation_1-rmse:0.16166
[30] validation_0-rmse:0.17371 validation_1-rmse:0.15983
[31] validation_0-rmse:0.17243 validation_1-rmse:0.15792
[32] validation_0-rmse:0.17110 validation_1-rmse:0.15628
[33] validation_0-rmse:0.16996 validation_1-rmse:0.15433
[34] validation_0-rmse:0.16884 validation_1-rmse:0.15277
[35] validation_0-rmse:0.16785 validation_1-rmse:0.15090
[36] validation_0-rmse:0.16682 validation_1-rmse:0.14942
[37] validation_0-rmse:0.16559 validation_1-rmse:0.14774
[38] validation_0-rmse:0.16459 validation_1-rmse:0.14628
[39] validation_0-rmse:0.16356 validation_1-rmse:0.14466
[40] validation_0-rmse:0.16250 validation_1-rmse:0.14330
[41] validation_0-rmse:0.16153 validation_1-rmse:0.14201
[42] validation_0-rmse:0.16059 validation_1-rmse:0.14075
[43] validation_0-rmse:0.15986 validation_1-rmse:0.13938
[44] validation_0-rmse:0.15908 validation_1-rmse:0.13822
[45] validation_0-rmse:0.15810 validation_1-rmse:0.13687
[46] validation_0-rmse:0.15733 validation_1-rmse:0.13577
[47] validation_0-rmse:0.15655 validation_1-rmse:0.13458
[48] validation_0-rmse:0.15580 validation_1-rmse:0.13355
[49] validation_0-rmse:0.15512 validation_1-rmse:0.13228
[50] validation_0-rmse:0.15434 validation_1-rmse:0.13121
[51] validation_0-rmse:0.15363 validation_1-rmse:0.13030
[52] validation_0-rmse:0.15294 validation_1-rmse:0.12937
[53] validation_0-rmse:0.15243 validation_1-rmse:0.12818
[54] validation_0-rmse:0.15170 validation_1-rmse:0.12720
[55] validation_0-rmse:0.15096 validation_1-rmse:0.12632
[56] validation_0-rmse:0.15035 validation_1-rmse:0.12538
[57] validation_0-rmse:0.14977 validation_1-rmse:0.12453
[58] validation_0-rmse:0.14914 validation_1-rmse:0.12363
[59] validation_0-rmse:0.14867 validation_1-rmse:0.12263
[60] validation_0-rmse:0.14819 validation_1-rmse:0.12183
[61] validation_0-rmse:0.14763 validation_1-rmse:0.12108
[62] validation_0-rmse:0.14706 validation_1-rmse:0.12035
[63] validation_0-rmse:0.14648 validation_1-rmse:0.11946
[64] validation_0-rmse:0.14601 validation_1-rmse:0.11876
[65] validation_0-rmse:0.14553 validation_1-rmse:0.11808
[66] validation_0-rmse:0.14506 validation_1-rmse:0.11742
[67] validation_0-rmse:0.14469 validation_1-rmse:0.11671
[68] validation_0-rmse:0.14422 validation_1-rmse:0.11604
[69] validation_0-rmse:0.14381 validation_1-rmse:0.11543
[70] validation_0-rmse:0.14337 validation_1-rmse:0.11485
[71] validation_0-rmse:0.14294 validation_1-rmse:0.11398
[72] validation_0-rmse:0.14260 validation_1-rmse:0.11335
[73] validation_0-rmse:0.14223 validation_1-rmse:0.11278
[74] validation_0-rmse:0.14190 validation_1-rmse:0.11225
[75] validation_0-rmse:0.14144 validation_1-rmse:0.11143
[76] validation_0-rmse:0.14098 validation_1-rmse:0.11052
[77] validation_0-rmse:0.14062 validation_1-rmse:0.10998
[78] validation_0-rmse:0.14029 validation_1-rmse:0.10953
[79] validation_0-rmse:0.13993 validation_1-rmse:0.10888
[80] validation_0-rmse:0.13958 validation_1-rmse:0.10839
[81] validation_0-rmse:0.13918 validation_1-rmse:0.10767
[82] validation_0-rmse:0.13897 validation_1-rmse:0.10720
[83] validation_0-rmse:0.13864 validation_1-rmse:0.10669
[84] validation_0-rmse:0.13836 validation_1-rmse:0.10620
[85] validation_0-rmse:0.13810 validation_1-rmse:0.10573
[86] validation_0-rmse:0.13782 validation_1-rmse:0.10526
[87] validation_0-rmse:0.13756 validation_1-rmse:0.10458
[88] validation_0-rmse:0.13736 validation_1-rmse:0.10420
[89] validation_0-rmse:0.13708 validation_1-rmse:0.10383
[90] validation_0-rmse:0.13685 validation_1-rmse:0.10343
[91] validation_0-rmse:0.13658 validation_1-rmse:0.10298
[92] validation_0-rmse:0.13646 validation_1-rmse:0.10231
[93] validation_0-rmse:0.13615 validation_1-rmse:0.10190
[94] validation_0-rmse:0.13589 validation_1-rmse:0.10154
[95] validation_0-rmse:0.13572 validation_1-rmse:0.10095
[96] validation_0-rmse:0.13550 validation_1-rmse:0.10058
[97] validation_0-rmse:0.13530 validation_1-rmse:0.10026
[98] validation_0-rmse:0.13513 validation_1-rmse:0.09995
[99] validation_0-rmse:0.13480 validation_1-rmse:0.09950
2025-04-29 01:22:16,022 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.74 secs) --------------------
2025-04-29 01:22:16,023 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:16,682 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2024-12-12 00:00:00 to 2025-01-11 00:00:00, 2/11 trains
2025-04-29 01:22:16,683 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1736553600_prediction.feather
2025-04-29 01:22:16,685 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:16,691 - FreqaiExampleStrategy - INFO - 目标列形状:(19250,)
2025-04-29 01:22:16,693 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.202701
1 0.003285 50.202701
2 0.001898 50.202701
3 0.000484 50.202701
4 0.001688 50.202701
2025-04-29 01:22:16,697 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:16,703 - FreqaiExampleStrategy - INFO - 目标列形状:(24050,)
2025-04-29 01:22:16,704 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.367593
1 0.003285 50.367593
2 0.001898 50.367593
3 0.000484 50.367593
4 0.001688 50.367593
2025-04-29 01:22:16,708 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1736553600/cb_btc_1736553600
2025-04-29 01:22:16,709 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:16,726 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:16,726 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2024-12-12 to 2025-01-10 --------------------
2025-04-29 01:22:21,650 - datasieve.pipeline - INFO - DI tossed 5 predictions for being too far from training data.
2025-04-29 01:22:21,652 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:21,652 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.26037 validation_1-rmse:0.25324
[1] validation_0-rmse:0.25572 validation_1-rmse:0.24787
[2] validation_0-rmse:0.25117 validation_1-rmse:0.24281
[3] validation_0-rmse:0.24697 validation_1-rmse:0.23802
[4] validation_0-rmse:0.24328 validation_1-rmse:0.23332
[5] validation_0-rmse:0.23939 validation_1-rmse:0.22905
[6] validation_0-rmse:0.23522 validation_1-rmse:0.22484
[7] validation_0-rmse:0.23148 validation_1-rmse:0.22085
[8] validation_0-rmse:0.22873 validation_1-rmse:0.21697
[9] validation_0-rmse:0.22519 validation_1-rmse:0.21317
[10] validation_0-rmse:0.22206 validation_1-rmse:0.20963
[11] validation_0-rmse:0.21866 validation_1-rmse:0.20626
[12] validation_0-rmse:0.21563 validation_1-rmse:0.20296
[13] validation_0-rmse:0.21313 validation_1-rmse:0.19956
[14] validation_0-rmse:0.21062 validation_1-rmse:0.19636
[15] validation_0-rmse:0.20808 validation_1-rmse:0.19339
[16] validation_0-rmse:0.20570 validation_1-rmse:0.19058
[17] validation_0-rmse:0.20318 validation_1-rmse:0.18781
[18] validation_0-rmse:0.20113 validation_1-rmse:0.18518
[19] validation_0-rmse:0.19934 validation_1-rmse:0.18248
[20] validation_0-rmse:0.19735 validation_1-rmse:0.18006
[21] validation_0-rmse:0.19541 validation_1-rmse:0.17744
[22] validation_0-rmse:0.19336 validation_1-rmse:0.17517
[23] validation_0-rmse:0.19145 validation_1-rmse:0.17301
[24] validation_0-rmse:0.18989 validation_1-rmse:0.17058
[25] validation_0-rmse:0.18782 validation_1-rmse:0.16854
[26] validation_0-rmse:0.18634 validation_1-rmse:0.16625
[27] validation_0-rmse:0.18471 validation_1-rmse:0.16430
[28] validation_0-rmse:0.18312 validation_1-rmse:0.16236
[29] validation_0-rmse:0.18157 validation_1-rmse:0.16053
[30] validation_0-rmse:0.17991 validation_1-rmse:0.15849
[31] validation_0-rmse:0.17839 validation_1-rmse:0.15677
[32] validation_0-rmse:0.17693 validation_1-rmse:0.15498
[33] validation_0-rmse:0.17574 validation_1-rmse:0.15336
[34] validation_0-rmse:0.17469 validation_1-rmse:0.15168
[35] validation_0-rmse:0.17352 validation_1-rmse:0.15015
[36] validation_0-rmse:0.17228 validation_1-rmse:0.14868
[37] validation_0-rmse:0.17127 validation_1-rmse:0.14692
[38] validation_0-rmse:0.17030 validation_1-rmse:0.14553
[39] validation_0-rmse:0.16926 validation_1-rmse:0.14420
[40] validation_0-rmse:0.16821 validation_1-rmse:0.14297
[41] validation_0-rmse:0.16740 validation_1-rmse:0.14144
[42] validation_0-rmse:0.16647 validation_1-rmse:0.14020
[43] validation_0-rmse:0.16548 validation_1-rmse:0.13903
[44] validation_0-rmse:0.16440 validation_1-rmse:0.13765
[45] validation_0-rmse:0.16353 validation_1-rmse:0.13652
[46] validation_0-rmse:0.16269 validation_1-rmse:0.13522
[47] validation_0-rmse:0.16193 validation_1-rmse:0.13419
[48] validation_0-rmse:0.16114 validation_1-rmse:0.13311
[49] validation_0-rmse:0.16043 validation_1-rmse:0.13214
[50] validation_0-rmse:0.15971 validation_1-rmse:0.13090
[51] validation_0-rmse:0.15909 validation_1-rmse:0.12992
[52] validation_0-rmse:0.15834 validation_1-rmse:0.12899
[53] validation_0-rmse:0.15763 validation_1-rmse:0.12809
[54] validation_0-rmse:0.15697 validation_1-rmse:0.12724
[55] validation_0-rmse:0.15631 validation_1-rmse:0.12637
[56] validation_0-rmse:0.15553 validation_1-rmse:0.12535
[57] validation_0-rmse:0.15494 validation_1-rmse:0.12456
[58] validation_0-rmse:0.15452 validation_1-rmse:0.12352
[59] validation_0-rmse:0.15396 validation_1-rmse:0.12273
[60] validation_0-rmse:0.15334 validation_1-rmse:0.12196
[61] validation_0-rmse:0.15274 validation_1-rmse:0.12123
[62] validation_0-rmse:0.15221 validation_1-rmse:0.12048
[63] validation_0-rmse:0.15176 validation_1-rmse:0.11953
[64] validation_0-rmse:0.15133 validation_1-rmse:0.11887
[65] validation_0-rmse:0.15080 validation_1-rmse:0.11796
[66] validation_0-rmse:0.15035 validation_1-rmse:0.11734
[67] validation_0-rmse:0.14995 validation_1-rmse:0.11667
[68] validation_0-rmse:0.14954 validation_1-rmse:0.11616
[69] validation_0-rmse:0.14916 validation_1-rmse:0.11535
[70] validation_0-rmse:0.14887 validation_1-rmse:0.11469
[71] validation_0-rmse:0.14854 validation_1-rmse:0.11408
[72] validation_0-rmse:0.14811 validation_1-rmse:0.11334
[73] validation_0-rmse:0.14766 validation_1-rmse:0.11278
[74] validation_0-rmse:0.14738 validation_1-rmse:0.11231
[75] validation_0-rmse:0.14697 validation_1-rmse:0.11184
[76] validation_0-rmse:0.14663 validation_1-rmse:0.11108
[77] validation_0-rmse:0.14635 validation_1-rmse:0.11058
[78] validation_0-rmse:0.14591 validation_1-rmse:0.10984
[79] validation_0-rmse:0.14561 validation_1-rmse:0.10929
[80] validation_0-rmse:0.14529 validation_1-rmse:0.10875
[81] validation_0-rmse:0.14510 validation_1-rmse:0.10826
[82] validation_0-rmse:0.14471 validation_1-rmse:0.10772
[83] validation_0-rmse:0.14444 validation_1-rmse:0.10725
[84] validation_0-rmse:0.14420 validation_1-rmse:0.10652
[85] validation_0-rmse:0.14393 validation_1-rmse:0.10608
[86] validation_0-rmse:0.14371 validation_1-rmse:0.10567
[87] validation_0-rmse:0.14342 validation_1-rmse:0.10528
[88] validation_0-rmse:0.14314 validation_1-rmse:0.10483
[89] validation_0-rmse:0.14307 validation_1-rmse:0.10439
[90] validation_0-rmse:0.14273 validation_1-rmse:0.10395
[91] validation_0-rmse:0.14237 validation_1-rmse:0.10353
[92] validation_0-rmse:0.14210 validation_1-rmse:0.10318
[93] validation_0-rmse:0.14186 validation_1-rmse:0.10279
[94] validation_0-rmse:0.14175 validation_1-rmse:0.10234
[95] validation_0-rmse:0.14153 validation_1-rmse:0.10204
[96] validation_0-rmse:0.14142 validation_1-rmse:0.10160
[97] validation_0-rmse:0.14124 validation_1-rmse:0.10126
[98] validation_0-rmse:0.14102 validation_1-rmse:0.10068
[99] validation_0-rmse:0.14079 validation_1-rmse:0.10036
2025-04-29 01:22:22,365 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.66 secs) --------------------
2025-04-29 01:22:22,366 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:22,973 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2024-12-22 00:00:00 to 2025-01-21 00:00:00, 3/11 trains
2025-04-29 01:22:22,973 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1737417600_prediction.feather
2025-04-29 01:22:22,978 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:22,983 - FreqaiExampleStrategy - INFO - 目标列形状:(24050,)
2025-04-29 01:22:22,985 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.367593
1 0.003285 50.367593
2 0.001898 50.367593
3 0.000484 50.367593
4 0.001688 50.367593
2025-04-29 01:22:22,989 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:22,995 - FreqaiExampleStrategy - INFO - 目标列形状:(28850,)
2025-04-29 01:22:22,996 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.305589
1 0.003285 50.305589
2 0.001898 50.305589
3 0.000484 50.305589
4 0.001688 50.305589
2025-04-29 01:22:23,001 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1737417600/cb_btc_1737417600
2025-04-29 01:22:23,001 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:23,018 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:23,019 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2024-12-22 to 2025-01-20 --------------------
2025-04-29 01:22:27,947 - datasieve.pipeline - INFO - DI tossed 1622 predictions for being too far from training data.
2025-04-29 01:22:27,950 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:27,951 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.25769 validation_1-rmse:0.25549
[1] validation_0-rmse:0.25314 validation_1-rmse:0.24986
[2] validation_0-rmse:0.24864 validation_1-rmse:0.24456
[3] validation_0-rmse:0.24486 validation_1-rmse:0.23955
[4] validation_0-rmse:0.24144 validation_1-rmse:0.23480
[5] validation_0-rmse:0.23803 validation_1-rmse:0.23024
[6] validation_0-rmse:0.23468 validation_1-rmse:0.22599
[7] validation_0-rmse:0.23134 validation_1-rmse:0.22162
[8] validation_0-rmse:0.22843 validation_1-rmse:0.21773
[9] validation_0-rmse:0.22560 validation_1-rmse:0.21396
[10] validation_0-rmse:0.22402 validation_1-rmse:0.21023
[11] validation_0-rmse:0.22155 validation_1-rmse:0.20680
[12] validation_0-rmse:0.21899 validation_1-rmse:0.20342
[13] validation_0-rmse:0.21654 validation_1-rmse:0.20029
[14] validation_0-rmse:0.21431 validation_1-rmse:0.19719
[15] validation_0-rmse:0.21282 validation_1-rmse:0.19411
[16] validation_0-rmse:0.21076 validation_1-rmse:0.19117
[17] validation_0-rmse:0.20882 validation_1-rmse:0.18835
[18] validation_0-rmse:0.20695 validation_1-rmse:0.18547
[19] validation_0-rmse:0.20538 validation_1-rmse:0.18292
[20] validation_0-rmse:0.20345 validation_1-rmse:0.18038
[21] validation_0-rmse:0.20148 validation_1-rmse:0.17799
[22] validation_0-rmse:0.19991 validation_1-rmse:0.17569
[23] validation_0-rmse:0.19832 validation_1-rmse:0.17350
[24] validation_0-rmse:0.19658 validation_1-rmse:0.17096
[25] validation_0-rmse:0.19474 validation_1-rmse:0.16879
[26] validation_0-rmse:0.19292 validation_1-rmse:0.16665
[27] validation_0-rmse:0.19134 validation_1-rmse:0.16470
[28] validation_0-rmse:0.19034 validation_1-rmse:0.16253
[29] validation_0-rmse:0.18882 validation_1-rmse:0.16068
[30] validation_0-rmse:0.18736 validation_1-rmse:0.15892
[31] validation_0-rmse:0.18605 validation_1-rmse:0.15690
[32] validation_0-rmse:0.18481 validation_1-rmse:0.15521
[33] validation_0-rmse:0.18346 validation_1-rmse:0.15356
[34] validation_0-rmse:0.18222 validation_1-rmse:0.15188
[35] validation_0-rmse:0.18095 validation_1-rmse:0.15028
[36] validation_0-rmse:0.18015 validation_1-rmse:0.14857
[37] validation_0-rmse:0.17915 validation_1-rmse:0.14713
[38] validation_0-rmse:0.17817 validation_1-rmse:0.14573
[39] validation_0-rmse:0.17723 validation_1-rmse:0.14437
[40] validation_0-rmse:0.17619 validation_1-rmse:0.14308
[41] validation_0-rmse:0.17509 validation_1-rmse:0.14176
[42] validation_0-rmse:0.17407 validation_1-rmse:0.14047
[43] validation_0-rmse:0.17340 validation_1-rmse:0.13921
[44] validation_0-rmse:0.17245 validation_1-rmse:0.13806
[45] validation_0-rmse:0.17212 validation_1-rmse:0.13685
[46] validation_0-rmse:0.17133 validation_1-rmse:0.13577
[47] validation_0-rmse:0.17064 validation_1-rmse:0.13451
[48] validation_0-rmse:0.17004 validation_1-rmse:0.13331
[49] validation_0-rmse:0.16941 validation_1-rmse:0.13222
[50] validation_0-rmse:0.16858 validation_1-rmse:0.13123
[51] validation_0-rmse:0.16786 validation_1-rmse:0.13007
[52] validation_0-rmse:0.16718 validation_1-rmse:0.12912
[53] validation_0-rmse:0.16651 validation_1-rmse:0.12806
[54] validation_0-rmse:0.16592 validation_1-rmse:0.12709
[55] validation_0-rmse:0.16542 validation_1-rmse:0.12604
[56] validation_0-rmse:0.16479 validation_1-rmse:0.12523
[57] validation_0-rmse:0.16426 validation_1-rmse:0.12439
[58] validation_0-rmse:0.16363 validation_1-rmse:0.12352
[59] validation_0-rmse:0.16325 validation_1-rmse:0.12263
[60] validation_0-rmse:0.16289 validation_1-rmse:0.12173
[61] validation_0-rmse:0.16226 validation_1-rmse:0.12099
[62] validation_0-rmse:0.16176 validation_1-rmse:0.12010
[63] validation_0-rmse:0.16144 validation_1-rmse:0.11936
[64] validation_0-rmse:0.16088 validation_1-rmse:0.11862
[65] validation_0-rmse:0.16030 validation_1-rmse:0.11786
[66] validation_0-rmse:0.15991 validation_1-rmse:0.11714
[67] validation_0-rmse:0.15947 validation_1-rmse:0.11640
[68] validation_0-rmse:0.15912 validation_1-rmse:0.11574
[69] validation_0-rmse:0.15874 validation_1-rmse:0.11507
[70] validation_0-rmse:0.15837 validation_1-rmse:0.11430
[71] validation_0-rmse:0.15798 validation_1-rmse:0.11365
[72] validation_0-rmse:0.15763 validation_1-rmse:0.11305
[73] validation_0-rmse:0.15713 validation_1-rmse:0.11250
[74] validation_0-rmse:0.15648 validation_1-rmse:0.11177
[75] validation_0-rmse:0.15619 validation_1-rmse:0.11122
[76] validation_0-rmse:0.15593 validation_1-rmse:0.11066
[77] validation_0-rmse:0.15562 validation_1-rmse:0.11007
[78] validation_0-rmse:0.15519 validation_1-rmse:0.10953
[79] validation_0-rmse:0.15500 validation_1-rmse:0.10883
[80] validation_0-rmse:0.15461 validation_1-rmse:0.10835
[81] validation_0-rmse:0.15417 validation_1-rmse:0.10780
[82] validation_0-rmse:0.15393 validation_1-rmse:0.10742
[83] validation_0-rmse:0.15395 validation_1-rmse:0.10634
[84] validation_0-rmse:0.15359 validation_1-rmse:0.10588
[85] validation_0-rmse:0.15315 validation_1-rmse:0.10539
[86] validation_0-rmse:0.15315 validation_1-rmse:0.10440
[87] validation_0-rmse:0.15278 validation_1-rmse:0.10400
[88] validation_0-rmse:0.15239 validation_1-rmse:0.10353
[89] validation_0-rmse:0.15200 validation_1-rmse:0.10310
[90] validation_0-rmse:0.15182 validation_1-rmse:0.10245
[91] validation_0-rmse:0.15175 validation_1-rmse:0.10182
[92] validation_0-rmse:0.15139 validation_1-rmse:0.10138
[93] validation_0-rmse:0.15105 validation_1-rmse:0.10095
[94] validation_0-rmse:0.15091 validation_1-rmse:0.10056
[95] validation_0-rmse:0.15088 validation_1-rmse:0.09964
[96] validation_0-rmse:0.15065 validation_1-rmse:0.09927
[97] validation_0-rmse:0.15036 validation_1-rmse:0.09888
[98] validation_0-rmse:0.15021 validation_1-rmse:0.09852
[99] validation_0-rmse:0.15004 validation_1-rmse:0.09815
2025-04-29 01:22:28,711 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.71 secs) --------------------
2025-04-29 01:22:28,712 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:29,220 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-01-01 00:00:00 to 2025-01-31 00:00:00, 4/11 trains
2025-04-29 01:22:29,221 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1738281600_prediction.feather
2025-04-29 01:22:29,226 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:29,231 - FreqaiExampleStrategy - INFO - 目标列形状:(28850,)
2025-04-29 01:22:29,233 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.305589
1 0.003285 50.305589
2 0.001898 50.305589
3 0.000484 50.305589
4 0.001688 50.305589
2025-04-29 01:22:29,239 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:29,245 - FreqaiExampleStrategy - INFO - 目标列形状:(33650,)
2025-04-29 01:22:29,246 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.168798
1 0.003285 50.168798
2 0.001898 50.168798
3 0.000484 50.168798
4 0.001688 50.168798
2025-04-29 01:22:29,251 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1738281600/cb_btc_1738281600
2025-04-29 01:22:29,251 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:29,267 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:29,268 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-01 to 2025-01-30 --------------------
2025-04-29 01:22:34,207 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:34,208 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.25046 validation_1-rmse:0.26128
[1] validation_0-rmse:0.24588 validation_1-rmse:0.25570
[2] validation_0-rmse:0.24156 validation_1-rmse:0.25047
[3] validation_0-rmse:0.23757 validation_1-rmse:0.24551
[4] validation_0-rmse:0.23411 validation_1-rmse:0.24075
[5] validation_0-rmse:0.23029 validation_1-rmse:0.23637
[6] validation_0-rmse:0.22707 validation_1-rmse:0.23199
[7] validation_0-rmse:0.22405 validation_1-rmse:0.22801
[8] validation_0-rmse:0.22083 validation_1-rmse:0.22420
[9] validation_0-rmse:0.21768 validation_1-rmse:0.22038
[10] validation_0-rmse:0.21473 validation_1-rmse:0.21674
[11] validation_0-rmse:0.21187 validation_1-rmse:0.21322
[12] validation_0-rmse:0.20911 validation_1-rmse:0.20996
[13] validation_0-rmse:0.20669 validation_1-rmse:0.20679
[14] validation_0-rmse:0.20441 validation_1-rmse:0.20366
[15] validation_0-rmse:0.20250 validation_1-rmse:0.20054
[16] validation_0-rmse:0.20017 validation_1-rmse:0.19757
[17] validation_0-rmse:0.19804 validation_1-rmse:0.19490
[18] validation_0-rmse:0.19618 validation_1-rmse:0.19221
[19] validation_0-rmse:0.19404 validation_1-rmse:0.18954
[20] validation_0-rmse:0.19209 validation_1-rmse:0.18666
[21] validation_0-rmse:0.19014 validation_1-rmse:0.18430
[22] validation_0-rmse:0.18845 validation_1-rmse:0.18197
[23] validation_0-rmse:0.18653 validation_1-rmse:0.17972
[24] validation_0-rmse:0.18468 validation_1-rmse:0.17722
[25] validation_0-rmse:0.18325 validation_1-rmse:0.17491
[26] validation_0-rmse:0.18152 validation_1-rmse:0.17284
[27] validation_0-rmse:0.17999 validation_1-rmse:0.17092
[28] validation_0-rmse:0.17846 validation_1-rmse:0.16892
[29] validation_0-rmse:0.17696 validation_1-rmse:0.16709
[30] validation_0-rmse:0.17558 validation_1-rmse:0.16510
[31] validation_0-rmse:0.17418 validation_1-rmse:0.16335
[32] validation_0-rmse:0.17293 validation_1-rmse:0.16161
[33] validation_0-rmse:0.17159 validation_1-rmse:0.16003
[34] validation_0-rmse:0.17030 validation_1-rmse:0.15831
[35] validation_0-rmse:0.16907 validation_1-rmse:0.15681
[36] validation_0-rmse:0.16796 validation_1-rmse:0.15513
[37] validation_0-rmse:0.16690 validation_1-rmse:0.15349
[38] validation_0-rmse:0.16580 validation_1-rmse:0.15204
[39] validation_0-rmse:0.16492 validation_1-rmse:0.15050
[40] validation_0-rmse:0.16383 validation_1-rmse:0.14918
[41] validation_0-rmse:0.16281 validation_1-rmse:0.14788
[42] validation_0-rmse:0.16176 validation_1-rmse:0.14660
[43] validation_0-rmse:0.16082 validation_1-rmse:0.14516
[44] validation_0-rmse:0.15990 validation_1-rmse:0.14395
[45] validation_0-rmse:0.15891 validation_1-rmse:0.14281
[46] validation_0-rmse:0.15797 validation_1-rmse:0.14168
[47] validation_0-rmse:0.15712 validation_1-rmse:0.14040
[48] validation_0-rmse:0.15632 validation_1-rmse:0.13933
[49] validation_0-rmse:0.15542 validation_1-rmse:0.13821
[50] validation_0-rmse:0.15458 validation_1-rmse:0.13705
[51] validation_0-rmse:0.15404 validation_1-rmse:0.13583
[52] validation_0-rmse:0.15334 validation_1-rmse:0.13483
[53] validation_0-rmse:0.15256 validation_1-rmse:0.13387
[54] validation_0-rmse:0.15190 validation_1-rmse:0.13290
[55] validation_0-rmse:0.15122 validation_1-rmse:0.13174
[56] validation_0-rmse:0.15065 validation_1-rmse:0.13080
[57] validation_0-rmse:0.15006 validation_1-rmse:0.12993
[58] validation_0-rmse:0.14955 validation_1-rmse:0.12897
[59] validation_0-rmse:0.14893 validation_1-rmse:0.12814
[60] validation_0-rmse:0.14843 validation_1-rmse:0.12735
[61] validation_0-rmse:0.14789 validation_1-rmse:0.12642
[62] validation_0-rmse:0.14718 validation_1-rmse:0.12561
[63] validation_0-rmse:0.14659 validation_1-rmse:0.12486
[64] validation_0-rmse:0.14600 validation_1-rmse:0.12397
[65] validation_0-rmse:0.14547 validation_1-rmse:0.12324
[66] validation_0-rmse:0.14499 validation_1-rmse:0.12255
[67] validation_0-rmse:0.14451 validation_1-rmse:0.12188
[68] validation_0-rmse:0.14393 validation_1-rmse:0.12114
[69] validation_0-rmse:0.14346 validation_1-rmse:0.12048
[70] validation_0-rmse:0.14293 validation_1-rmse:0.11974
[71] validation_0-rmse:0.14256 validation_1-rmse:0.11893
[72] validation_0-rmse:0.14212 validation_1-rmse:0.11830
[73] validation_0-rmse:0.14177 validation_1-rmse:0.11748
[74] validation_0-rmse:0.14134 validation_1-rmse:0.11686
[75] validation_0-rmse:0.14101 validation_1-rmse:0.11609
[76] validation_0-rmse:0.14060 validation_1-rmse:0.11536
[77] validation_0-rmse:0.14020 validation_1-rmse:0.11484
[78] validation_0-rmse:0.13983 validation_1-rmse:0.11412
[79] validation_0-rmse:0.13951 validation_1-rmse:0.11357
[80] validation_0-rmse:0.13928 validation_1-rmse:0.11273
[81] validation_0-rmse:0.13889 validation_1-rmse:0.11221
[82] validation_0-rmse:0.13855 validation_1-rmse:0.11166
[83] validation_0-rmse:0.13824 validation_1-rmse:0.11114
[84] validation_0-rmse:0.13808 validation_1-rmse:0.11050
[85] validation_0-rmse:0.13767 validation_1-rmse:0.10998
[86] validation_0-rmse:0.13731 validation_1-rmse:0.10947
[87] validation_0-rmse:0.13716 validation_1-rmse:0.10876
[88] validation_0-rmse:0.13678 validation_1-rmse:0.10832
[89] validation_0-rmse:0.13659 validation_1-rmse:0.10782
[90] validation_0-rmse:0.13629 validation_1-rmse:0.10736
[91] validation_0-rmse:0.13600 validation_1-rmse:0.10662
[92] validation_0-rmse:0.13577 validation_1-rmse:0.10613
[93] validation_0-rmse:0.13541 validation_1-rmse:0.10565
[94] validation_0-rmse:0.13534 validation_1-rmse:0.10501
[95] validation_0-rmse:0.13511 validation_1-rmse:0.10453
[96] validation_0-rmse:0.13483 validation_1-rmse:0.10401
[97] validation_0-rmse:0.13455 validation_1-rmse:0.10362
[98] validation_0-rmse:0.13425 validation_1-rmse:0.10323
[99] validation_0-rmse:0.13402 validation_1-rmse:0.10289
2025-04-29 01:22:35,089 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.84 secs) --------------------
2025-04-29 01:22:35,090 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:35,631 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-01-11 00:00:00 to 2025-02-10 00:00:00, 5/11 trains
2025-04-29 01:22:35,632 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1739145600_prediction.feather
2025-04-29 01:22:35,636 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:35,642 - FreqaiExampleStrategy - INFO - 目标列形状:(33650,)
2025-04-29 01:22:35,644 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.168798
1 0.003285 50.168798
2 0.001898 50.168798
3 0.000484 50.168798
4 0.001688 50.168798
2025-04-29 01:22:35,648 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:35,654 - FreqaiExampleStrategy - INFO - 目标列形状:(38450,)
2025-04-29 01:22:35,656 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.167897
1 0.003285 50.167897
2 0.001898 50.167897
3 0.000484 50.167897
4 0.001688 50.167897
2025-04-29 01:22:35,660 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1739145600/cb_btc_1739145600
2025-04-29 01:22:35,660 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:35,677 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:35,677 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-11 to 2025-02-09 --------------------
2025-04-29 01:22:40,681 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:40,682 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.26428 validation_1-rmse:0.27464
[1] validation_0-rmse:0.25911 validation_1-rmse:0.26865
[2] validation_0-rmse:0.25427 validation_1-rmse:0.26296
[3] validation_0-rmse:0.24970 validation_1-rmse:0.25748
[4] validation_0-rmse:0.24525 validation_1-rmse:0.25222
[5] validation_0-rmse:0.24140 validation_1-rmse:0.24725
[6] validation_0-rmse:0.23748 validation_1-rmse:0.24264
[7] validation_0-rmse:0.23368 validation_1-rmse:0.23792
[8] validation_0-rmse:0.23022 validation_1-rmse:0.23363
[9] validation_0-rmse:0.22695 validation_1-rmse:0.22945
[10] validation_0-rmse:0.22381 validation_1-rmse:0.22543
[11] validation_0-rmse:0.22105 validation_1-rmse:0.22154
[12] validation_0-rmse:0.21818 validation_1-rmse:0.21797
[13] validation_0-rmse:0.21526 validation_1-rmse:0.21430
[14] validation_0-rmse:0.21284 validation_1-rmse:0.21101
[15] validation_0-rmse:0.21034 validation_1-rmse:0.20769
[16] validation_0-rmse:0.20802 validation_1-rmse:0.20438
[17] validation_0-rmse:0.20590 validation_1-rmse:0.20136
[18] validation_0-rmse:0.20386 validation_1-rmse:0.19837
[19] validation_0-rmse:0.20219 validation_1-rmse:0.19549
[20] validation_0-rmse:0.20037 validation_1-rmse:0.19283
[21] validation_0-rmse:0.19826 validation_1-rmse:0.19005
[22] validation_0-rmse:0.19657 validation_1-rmse:0.18750
[23] validation_0-rmse:0.19525 validation_1-rmse:0.18498
[24] validation_0-rmse:0.19373 validation_1-rmse:0.18267
[25] validation_0-rmse:0.19197 validation_1-rmse:0.18037
[26] validation_0-rmse:0.19063 validation_1-rmse:0.17799
[27] validation_0-rmse:0.18897 validation_1-rmse:0.17587
[28] validation_0-rmse:0.18765 validation_1-rmse:0.17382
[29] validation_0-rmse:0.18608 validation_1-rmse:0.17185
[30] validation_0-rmse:0.18456 validation_1-rmse:0.16992
[31] validation_0-rmse:0.18340 validation_1-rmse:0.16793
[32] validation_0-rmse:0.18206 validation_1-rmse:0.16616
[33] validation_0-rmse:0.18077 validation_1-rmse:0.16437
[34] validation_0-rmse:0.17960 validation_1-rmse:0.16270
[35] validation_0-rmse:0.17857 validation_1-rmse:0.16105
[36] validation_0-rmse:0.17748 validation_1-rmse:0.15925
[37] validation_0-rmse:0.17649 validation_1-rmse:0.15762
[38] validation_0-rmse:0.17540 validation_1-rmse:0.15611
[39] validation_0-rmse:0.17427 validation_1-rmse:0.15469
[40] validation_0-rmse:0.17312 validation_1-rmse:0.15301
[41] validation_0-rmse:0.17217 validation_1-rmse:0.15169
[42] validation_0-rmse:0.17119 validation_1-rmse:0.15037
[43] validation_0-rmse:0.17030 validation_1-rmse:0.14910
[44] validation_0-rmse:0.16939 validation_1-rmse:0.14786
[45] validation_0-rmse:0.16851 validation_1-rmse:0.14660
[46] validation_0-rmse:0.16793 validation_1-rmse:0.14518
[47] validation_0-rmse:0.16760 validation_1-rmse:0.14365
[48] validation_0-rmse:0.16674 validation_1-rmse:0.14258
[49] validation_0-rmse:0.16588 validation_1-rmse:0.14152
[50] validation_0-rmse:0.16505 validation_1-rmse:0.14051
[51] validation_0-rmse:0.16437 validation_1-rmse:0.13919
[52] validation_0-rmse:0.16361 validation_1-rmse:0.13818
[53] validation_0-rmse:0.16290 validation_1-rmse:0.13715
[54] validation_0-rmse:0.16217 validation_1-rmse:0.13621
[55] validation_0-rmse:0.16207 validation_1-rmse:0.13493
[56] validation_0-rmse:0.16153 validation_1-rmse:0.13395
[57] validation_0-rmse:0.16077 validation_1-rmse:0.13302
[58] validation_0-rmse:0.16021 validation_1-rmse:0.13218
[59] validation_0-rmse:0.15972 validation_1-rmse:0.13117
[60] validation_0-rmse:0.15954 validation_1-rmse:0.13003
[61] validation_0-rmse:0.15896 validation_1-rmse:0.12926
[62] validation_0-rmse:0.15849 validation_1-rmse:0.12848
[63] validation_0-rmse:0.15801 validation_1-rmse:0.12770
[64] validation_0-rmse:0.15737 validation_1-rmse:0.12678
[65] validation_0-rmse:0.15736 validation_1-rmse:0.12578
[66] validation_0-rmse:0.15684 validation_1-rmse:0.12506
[67] validation_0-rmse:0.15638 validation_1-rmse:0.12437
[68] validation_0-rmse:0.15618 validation_1-rmse:0.12336
[69] validation_0-rmse:0.15581 validation_1-rmse:0.12269
[70] validation_0-rmse:0.15537 validation_1-rmse:0.12205
[71] validation_0-rmse:0.15534 validation_1-rmse:0.12117
[72] validation_0-rmse:0.15485 validation_1-rmse:0.12049
[73] validation_0-rmse:0.15465 validation_1-rmse:0.11968
[74] validation_0-rmse:0.15430 validation_1-rmse:0.11906
[75] validation_0-rmse:0.15386 validation_1-rmse:0.11840
[76] validation_0-rmse:0.15353 validation_1-rmse:0.11781
[77] validation_0-rmse:0.15354 validation_1-rmse:0.11697
[78] validation_0-rmse:0.15325 validation_1-rmse:0.11630
[79] validation_0-rmse:0.15282 validation_1-rmse:0.11572
[80] validation_0-rmse:0.15239 validation_1-rmse:0.11514
[81] validation_0-rmse:0.15226 validation_1-rmse:0.11431
[82] validation_0-rmse:0.15189 validation_1-rmse:0.11381
[83] validation_0-rmse:0.15171 validation_1-rmse:0.11316
[84] validation_0-rmse:0.15136 validation_1-rmse:0.11270
[85] validation_0-rmse:0.15112 validation_1-rmse:0.11212
[86] validation_0-rmse:0.15112 validation_1-rmse:0.11140
[87] validation_0-rmse:0.15074 validation_1-rmse:0.11094
[88] validation_0-rmse:0.15048 validation_1-rmse:0.11035
[89] validation_0-rmse:0.15026 validation_1-rmse:0.10983
[90] validation_0-rmse:0.14989 validation_1-rmse:0.10938
[91] validation_0-rmse:0.14955 validation_1-rmse:0.10893
[92] validation_0-rmse:0.14955 validation_1-rmse:0.10815
[93] validation_0-rmse:0.14933 validation_1-rmse:0.10765
[94] validation_0-rmse:0.14908 validation_1-rmse:0.10711
[95] validation_0-rmse:0.14889 validation_1-rmse:0.10668
[96] validation_0-rmse:0.14853 validation_1-rmse:0.10627
[97] validation_0-rmse:0.14853 validation_1-rmse:0.10553
[98] validation_0-rmse:0.14835 validation_1-rmse:0.10513
[99] validation_0-rmse:0.14818 validation_1-rmse:0.10475
2025-04-29 01:22:41,413 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.75 secs) --------------------
2025-04-29 01:22:41,414 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:41,936 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-01-21 00:00:00 to 2025-02-20 00:00:00, 6/11 trains
2025-04-29 01:22:41,937 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1740009600_prediction.feather
2025-04-29 01:22:41,941 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:41,948 - FreqaiExampleStrategy - INFO - 目标列形状:(38450,)
2025-04-29 01:22:41,949 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.167897
1 0.003285 50.167897
2 0.001898 50.167897
3 0.000484 50.167897
4 0.001688 50.167897
2025-04-29 01:22:41,954 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:41,961 - FreqaiExampleStrategy - INFO - 目标列形状:(43250,)
2025-04-29 01:22:41,962 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.107698
1 0.003285 50.107698
2 0.001898 50.107698
3 0.000484 50.107698
4 0.001688 50.107698
2025-04-29 01:22:41,967 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1740009600/cb_btc_1740009600
2025-04-29 01:22:41,967 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:41,983 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:41,984 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-21 to 2025-02-19 --------------------
2025-04-29 01:22:47,004 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:47,005 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.27166 validation_1-rmse:0.27726
[1] validation_0-rmse:0.26708 validation_1-rmse:0.27112
[2] validation_0-rmse:0.26297 validation_1-rmse:0.26523
[3] validation_0-rmse:0.25865 validation_1-rmse:0.25959
[4] validation_0-rmse:0.25494 validation_1-rmse:0.25419
[5] validation_0-rmse:0.25100 validation_1-rmse:0.24913
[6] validation_0-rmse:0.24763 validation_1-rmse:0.24437
[7] validation_0-rmse:0.24441 validation_1-rmse:0.23970
[8] validation_0-rmse:0.24110 validation_1-rmse:0.23527
[9] validation_0-rmse:0.23801 validation_1-rmse:0.23102
[10] validation_0-rmse:0.23492 validation_1-rmse:0.22691
[11] validation_0-rmse:0.23229 validation_1-rmse:0.22297
[12] validation_0-rmse:0.22956 validation_1-rmse:0.21923
[13] validation_0-rmse:0.22707 validation_1-rmse:0.21564
[14] validation_0-rmse:0.22482 validation_1-rmse:0.21221
[15] validation_0-rmse:0.22237 validation_1-rmse:0.20891
[16] validation_0-rmse:0.22030 validation_1-rmse:0.20557
[17] validation_0-rmse:0.21784 validation_1-rmse:0.20243
[18] validation_0-rmse:0.21591 validation_1-rmse:0.19949
[19] validation_0-rmse:0.21399 validation_1-rmse:0.19664
[20] validation_0-rmse:0.21182 validation_1-rmse:0.19378
[21] validation_0-rmse:0.20992 validation_1-rmse:0.19110
[22] validation_0-rmse:0.20821 validation_1-rmse:0.18850
[23] validation_0-rmse:0.20621 validation_1-rmse:0.18597
[24] validation_0-rmse:0.20490 validation_1-rmse:0.18353
[25] validation_0-rmse:0.20318 validation_1-rmse:0.18126
[26] validation_0-rmse:0.20168 validation_1-rmse:0.17896
[27] validation_0-rmse:0.19992 validation_1-rmse:0.17679
[28] validation_0-rmse:0.19865 validation_1-rmse:0.17458
[29] validation_0-rmse:0.19722 validation_1-rmse:0.17257
[30] validation_0-rmse:0.19571 validation_1-rmse:0.17039
[31] validation_0-rmse:0.19429 validation_1-rmse:0.16855
[32] validation_0-rmse:0.19285 validation_1-rmse:0.16664
[33] validation_0-rmse:0.19141 validation_1-rmse:0.16488
[34] validation_0-rmse:0.19022 validation_1-rmse:0.16312
[35] validation_0-rmse:0.18904 validation_1-rmse:0.16145
[36] validation_0-rmse:0.18832 validation_1-rmse:0.15973
[37] validation_0-rmse:0.18723 validation_1-rmse:0.15815
[38] validation_0-rmse:0.18610 validation_1-rmse:0.15653
[39] validation_0-rmse:0.18504 validation_1-rmse:0.15503
[40] validation_0-rmse:0.18402 validation_1-rmse:0.15358
[41] validation_0-rmse:0.18333 validation_1-rmse:0.15193
[42] validation_0-rmse:0.18213 validation_1-rmse:0.15058
[43] validation_0-rmse:0.18176 validation_1-rmse:0.14922
[44] validation_0-rmse:0.18093 validation_1-rmse:0.14792
[45] validation_0-rmse:0.18017 validation_1-rmse:0.14667
[46] validation_0-rmse:0.17928 validation_1-rmse:0.14537
[47] validation_0-rmse:0.17858 validation_1-rmse:0.14420
[48] validation_0-rmse:0.17770 validation_1-rmse:0.14306
[49] validation_0-rmse:0.17695 validation_1-rmse:0.14199
[50] validation_0-rmse:0.17613 validation_1-rmse:0.14094
[51] validation_0-rmse:0.17545 validation_1-rmse:0.13979
[52] validation_0-rmse:0.17490 validation_1-rmse:0.13874
[53] validation_0-rmse:0.17452 validation_1-rmse:0.13755
[54] validation_0-rmse:0.17383 validation_1-rmse:0.13663
[55] validation_0-rmse:0.17327 validation_1-rmse:0.13568
[56] validation_0-rmse:0.17255 validation_1-rmse:0.13477
[57] validation_0-rmse:0.17192 validation_1-rmse:0.13382
[58] validation_0-rmse:0.17138 validation_1-rmse:0.13277
[59] validation_0-rmse:0.17074 validation_1-rmse:0.13188
[60] validation_0-rmse:0.17026 validation_1-rmse:0.13089
[61] validation_0-rmse:0.16969 validation_1-rmse:0.13010
[62] validation_0-rmse:0.16932 validation_1-rmse:0.12904
[63] validation_0-rmse:0.16888 validation_1-rmse:0.12818
[64] validation_0-rmse:0.16849 validation_1-rmse:0.12745
[65] validation_0-rmse:0.16802 validation_1-rmse:0.12639
[66] validation_0-rmse:0.16747 validation_1-rmse:0.12567
[67] validation_0-rmse:0.16710 validation_1-rmse:0.12496
[68] validation_0-rmse:0.16672 validation_1-rmse:0.12426
[69] validation_0-rmse:0.16635 validation_1-rmse:0.12331
[70] validation_0-rmse:0.16597 validation_1-rmse:0.12267
[71] validation_0-rmse:0.16554 validation_1-rmse:0.12196
[72] validation_0-rmse:0.16522 validation_1-rmse:0.12121
[73] validation_0-rmse:0.16481 validation_1-rmse:0.12054
[74] validation_0-rmse:0.16442 validation_1-rmse:0.11996
[75] validation_0-rmse:0.16409 validation_1-rmse:0.11939
[76] validation_0-rmse:0.16375 validation_1-rmse:0.11878
[77] validation_0-rmse:0.16275 validation_1-rmse:0.11753
[78] validation_0-rmse:0.16248 validation_1-rmse:0.11692
[79] validation_0-rmse:0.16215 validation_1-rmse:0.11619
[80] validation_0-rmse:0.16187 validation_1-rmse:0.11564
[81] validation_0-rmse:0.16150 validation_1-rmse:0.11493
[82] validation_0-rmse:0.16123 validation_1-rmse:0.11438
[83] validation_0-rmse:0.16109 validation_1-rmse:0.11358
[84] validation_0-rmse:0.16065 validation_1-rmse:0.11304
[85] validation_0-rmse:0.16038 validation_1-rmse:0.11256
[86] validation_0-rmse:0.16022 validation_1-rmse:0.11205
[87] validation_0-rmse:0.16007 validation_1-rmse:0.11158
[88] validation_0-rmse:0.15945 validation_1-rmse:0.11054
[89] validation_0-rmse:0.15912 validation_1-rmse:0.11008
[90] validation_0-rmse:0.15894 validation_1-rmse:0.10937
[91] validation_0-rmse:0.15868 validation_1-rmse:0.10886
[92] validation_0-rmse:0.15845 validation_1-rmse:0.10844
[93] validation_0-rmse:0.15817 validation_1-rmse:0.10803
[94] validation_0-rmse:0.15789 validation_1-rmse:0.10758
[95] validation_0-rmse:0.15772 validation_1-rmse:0.10721
[96] validation_0-rmse:0.15763 validation_1-rmse:0.10676
[97] validation_0-rmse:0.15751 validation_1-rmse:0.10609
[98] validation_0-rmse:0.15731 validation_1-rmse:0.10574
[99] validation_0-rmse:0.15738 validation_1-rmse:0.10531
2025-04-29 01:22:47,782 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.81 secs) --------------------
2025-04-29 01:22:47,783 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:48,337 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-01-31 00:00:00 to 2025-03-02 00:00:00, 7/11 trains
2025-04-29 01:22:48,337 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1740873600_prediction.feather
2025-04-29 01:22:48,342 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:48,349 - FreqaiExampleStrategy - INFO - 目标列形状:(43250,)
2025-04-29 01:22:48,350 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.107698
1 0.003285 50.107698
2 0.001898 50.107698
3 0.000484 50.107698
4 0.001688 50.107698
2025-04-29 01:22:48,356 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:48,362 - FreqaiExampleStrategy - INFO - 目标列形状:(48050,)
2025-04-29 01:22:48,364 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.079166
1 0.003285 50.079166
2 0.001898 50.079166
3 0.000484 50.079166
4 0.001688 50.079166
2025-04-29 01:22:48,368 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1740873600/cb_btc_1740873600
2025-04-29 01:22:48,369 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:48,384 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:48,385 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-31 to 2025-03-01 --------------------
2025-04-29 01:22:53,444 - datasieve.pipeline - INFO - DI tossed 2275 predictions for being too far from training data.
2025-04-29 01:22:53,447 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:53,448 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.27618 validation_1-rmse:0.28955
[1] validation_0-rmse:0.27005 validation_1-rmse:0.28323
[2] validation_0-rmse:0.26414 validation_1-rmse:0.27722
[3] validation_0-rmse:0.25897 validation_1-rmse:0.27161
[4] validation_0-rmse:0.25425 validation_1-rmse:0.26622
[5] validation_0-rmse:0.24886 validation_1-rmse:0.26100
[6] validation_0-rmse:0.24522 validation_1-rmse:0.25606
[7] validation_0-rmse:0.24137 validation_1-rmse:0.25132
[8] validation_0-rmse:0.23765 validation_1-rmse:0.24687
[9] validation_0-rmse:0.23323 validation_1-rmse:0.24254
[10] validation_0-rmse:0.22900 validation_1-rmse:0.23827
[11] validation_0-rmse:0.22588 validation_1-rmse:0.23450
[12] validation_0-rmse:0.22228 validation_1-rmse:0.23055
[13] validation_0-rmse:0.21872 validation_1-rmse:0.22698
[14] validation_0-rmse:0.21492 validation_1-rmse:0.22348
[15] validation_0-rmse:0.21329 validation_1-rmse:0.22011
[16] validation_0-rmse:0.21024 validation_1-rmse:0.21686
[17] validation_0-rmse:0.20823 validation_1-rmse:0.21380
[18] validation_0-rmse:0.20544 validation_1-rmse:0.21075
[19] validation_0-rmse:0.20415 validation_1-rmse:0.20787
[20] validation_0-rmse:0.20143 validation_1-rmse:0.20515
[21] validation_0-rmse:0.19917 validation_1-rmse:0.20247
[22] validation_0-rmse:0.19745 validation_1-rmse:0.19994
[23] validation_0-rmse:0.19508 validation_1-rmse:0.19746
[24] validation_0-rmse:0.19300 validation_1-rmse:0.19490
[25] validation_0-rmse:0.19085 validation_1-rmse:0.19254
[26] validation_0-rmse:0.18898 validation_1-rmse:0.19031
[27] validation_0-rmse:0.18720 validation_1-rmse:0.18794
[28] validation_0-rmse:0.18503 validation_1-rmse:0.18584
[29] validation_0-rmse:0.18314 validation_1-rmse:0.18382
[30] validation_0-rmse:0.18132 validation_1-rmse:0.18164
[31] validation_0-rmse:0.17984 validation_1-rmse:0.17967
[32] validation_0-rmse:0.17818 validation_1-rmse:0.17779
[33] validation_0-rmse:0.17637 validation_1-rmse:0.17572
[34] validation_0-rmse:0.17473 validation_1-rmse:0.17399
[35] validation_0-rmse:0.17338 validation_1-rmse:0.17229
[36] validation_0-rmse:0.17253 validation_1-rmse:0.17055
[37] validation_0-rmse:0.17149 validation_1-rmse:0.16883
[38] validation_0-rmse:0.17030 validation_1-rmse:0.16730
[39] validation_0-rmse:0.16950 validation_1-rmse:0.16556
[40] validation_0-rmse:0.16815 validation_1-rmse:0.16412
[41] validation_0-rmse:0.16704 validation_1-rmse:0.16268
[42] validation_0-rmse:0.16617 validation_1-rmse:0.16128
[43] validation_0-rmse:0.16542 validation_1-rmse:0.15970
[44] validation_0-rmse:0.16438 validation_1-rmse:0.15840
[45] validation_0-rmse:0.16356 validation_1-rmse:0.15692
[46] validation_0-rmse:0.16239 validation_1-rmse:0.15574
[47] validation_0-rmse:0.16153 validation_1-rmse:0.15456
[48] validation_0-rmse:0.16076 validation_1-rmse:0.15314
[49] validation_0-rmse:0.15998 validation_1-rmse:0.15201
[50] validation_0-rmse:0.15946 validation_1-rmse:0.15084
[51] validation_0-rmse:0.15891 validation_1-rmse:0.14954
[52] validation_0-rmse:0.15834 validation_1-rmse:0.14847
[53] validation_0-rmse:0.15764 validation_1-rmse:0.14722
[54] validation_0-rmse:0.15707 validation_1-rmse:0.14623
[55] validation_0-rmse:0.15653 validation_1-rmse:0.14527
[56] validation_0-rmse:0.15583 validation_1-rmse:0.14434
[57] validation_0-rmse:0.15549 validation_1-rmse:0.14329
[58] validation_0-rmse:0.15507 validation_1-rmse:0.14241
[59] validation_0-rmse:0.15468 validation_1-rmse:0.14053
[60] validation_0-rmse:0.15398 validation_1-rmse:0.13968
[61] validation_0-rmse:0.15390 validation_1-rmse:0.13864
[62] validation_0-rmse:0.15360 validation_1-rmse:0.13783
[63] validation_0-rmse:0.15368 validation_1-rmse:0.13704
[64] validation_0-rmse:0.15338 validation_1-rmse:0.13624
[65] validation_0-rmse:0.15273 validation_1-rmse:0.13551
[66] validation_0-rmse:0.15238 validation_1-rmse:0.13451
[67] validation_0-rmse:0.15212 validation_1-rmse:0.13290
[68] validation_0-rmse:0.15191 validation_1-rmse:0.13217
[69] validation_0-rmse:0.15138 validation_1-rmse:0.13143
[70] validation_0-rmse:0.15090 validation_1-rmse:0.13071
[71] validation_0-rmse:0.15082 validation_1-rmse:0.13001
[72] validation_0-rmse:0.14988 validation_1-rmse:0.12847
[73] validation_0-rmse:0.14953 validation_1-rmse:0.12783
[74] validation_0-rmse:0.14924 validation_1-rmse:0.12709
[75] validation_0-rmse:0.14926 validation_1-rmse:0.12578
[76] validation_0-rmse:0.14903 validation_1-rmse:0.12499
[77] validation_0-rmse:0.14851 validation_1-rmse:0.12435
[78] validation_0-rmse:0.14808 validation_1-rmse:0.12368
[79] validation_0-rmse:0.14768 validation_1-rmse:0.12305
[80] validation_0-rmse:0.14741 validation_1-rmse:0.12217
[81] validation_0-rmse:0.14712 validation_1-rmse:0.12165
[82] validation_0-rmse:0.14696 validation_1-rmse:0.12110
[83] validation_0-rmse:0.14686 validation_1-rmse:0.12045
[84] validation_0-rmse:0.14648 validation_1-rmse:0.11984
[85] validation_0-rmse:0.14623 validation_1-rmse:0.11923
[86] validation_0-rmse:0.14606 validation_1-rmse:0.11869
[87] validation_0-rmse:0.14583 validation_1-rmse:0.11754
[88] validation_0-rmse:0.14572 validation_1-rmse:0.11710
[89] validation_0-rmse:0.14537 validation_1-rmse:0.11660
[90] validation_0-rmse:0.14510 validation_1-rmse:0.11614
[91] validation_0-rmse:0.14516 validation_1-rmse:0.11514
[92] validation_0-rmse:0.14480 validation_1-rmse:0.11455
[93] validation_0-rmse:0.14475 validation_1-rmse:0.11414
[94] validation_0-rmse:0.14443 validation_1-rmse:0.11374
[95] validation_0-rmse:0.14409 validation_1-rmse:0.11331
[96] validation_0-rmse:0.14391 validation_1-rmse:0.11240
[97] validation_0-rmse:0.14303 validation_1-rmse:0.11154
[98] validation_0-rmse:0.14274 validation_1-rmse:0.11114
[99] validation_0-rmse:0.14246 validation_1-rmse:0.11071
2025-04-29 01:22:54,188 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.82 secs) --------------------
2025-04-29 01:22:54,189 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:22:54,678 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-02-10 00:00:00 to 2025-03-12 00:00:00, 8/11 trains
2025-04-29 01:22:54,678 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1741737600_prediction.feather
2025-04-29 01:22:54,685 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:54,691 - FreqaiExampleStrategy - INFO - 目标列形状:(48050,)
2025-04-29 01:22:54,693 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.079166
1 0.003285 50.079166
2 0.001898 50.079166
3 0.000484 50.079166
4 0.001688 50.079166
2025-04-29 01:22:54,699 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:22:54,706 - FreqaiExampleStrategy - INFO - 目标列形状:(52850,)
2025-04-29 01:22:54,707 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.102027
1 0.003285 50.102027
2 0.001898 50.102027
3 0.000484 50.102027
4 0.001688 50.102027
2025-04-29 01:22:54,712 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1741737600/cb_btc_1741737600
2025-04-29 01:22:54,712 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:22:54,728 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:22:54,729 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-02-10 to 2025-03-11 --------------------
2025-04-29 01:22:59,740 - datasieve.pipeline - INFO - DI tossed 18 predictions for being too far from training data.
2025-04-29 01:22:59,743 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:22:59,743 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.26738 validation_1-rmse:0.26816
[1] validation_0-rmse:0.26268 validation_1-rmse:0.26258
[2] validation_0-rmse:0.25808 validation_1-rmse:0.25725
[3] validation_0-rmse:0.25395 validation_1-rmse:0.25212
[4] validation_0-rmse:0.24987 validation_1-rmse:0.24723
[5] validation_0-rmse:0.24633 validation_1-rmse:0.24263
[6] validation_0-rmse:0.24308 validation_1-rmse:0.23814
[7] validation_0-rmse:0.23959 validation_1-rmse:0.23402
[8] validation_0-rmse:0.23612 validation_1-rmse:0.22977
[9] validation_0-rmse:0.23322 validation_1-rmse:0.22577
[10] validation_0-rmse:0.23012 validation_1-rmse:0.22207
[11] validation_0-rmse:0.22730 validation_1-rmse:0.21843
[12] validation_0-rmse:0.22453 validation_1-rmse:0.21489
[13] validation_0-rmse:0.22236 validation_1-rmse:0.21145
[14] validation_0-rmse:0.22000 validation_1-rmse:0.20841
[15] validation_0-rmse:0.21744 validation_1-rmse:0.20529
[16] validation_0-rmse:0.21556 validation_1-rmse:0.20225
[17] validation_0-rmse:0.21331 validation_1-rmse:0.19932
[18] validation_0-rmse:0.21171 validation_1-rmse:0.19643
[19] validation_0-rmse:0.21051 validation_1-rmse:0.19382
[20] validation_0-rmse:0.20880 validation_1-rmse:0.19128
[21] validation_0-rmse:0.20711 validation_1-rmse:0.18854
[22] validation_0-rmse:0.20538 validation_1-rmse:0.18612
[23] validation_0-rmse:0.20350 validation_1-rmse:0.18381
[24] validation_0-rmse:0.20234 validation_1-rmse:0.18144
[25] validation_0-rmse:0.20081 validation_1-rmse:0.17917
[26] validation_0-rmse:0.19918 validation_1-rmse:0.17714
[27] validation_0-rmse:0.19804 validation_1-rmse:0.17496
[28] validation_0-rmse:0.19662 validation_1-rmse:0.17304
[29] validation_0-rmse:0.19580 validation_1-rmse:0.17082
[30] validation_0-rmse:0.19454 validation_1-rmse:0.16901
[31] validation_0-rmse:0.19331 validation_1-rmse:0.16691
[32] validation_0-rmse:0.19234 validation_1-rmse:0.16517
[33] validation_0-rmse:0.19118 validation_1-rmse:0.16354
[34] validation_0-rmse:0.19024 validation_1-rmse:0.16175
[35] validation_0-rmse:0.18915 validation_1-rmse:0.16020
[36] validation_0-rmse:0.18823 validation_1-rmse:0.15865
[37] validation_0-rmse:0.18756 validation_1-rmse:0.15712
[38] validation_0-rmse:0.18698 validation_1-rmse:0.15541
[39] validation_0-rmse:0.18643 validation_1-rmse:0.15395
[40] validation_0-rmse:0.18562 validation_1-rmse:0.15265
[41] validation_0-rmse:0.18516 validation_1-rmse:0.15124
[42] validation_0-rmse:0.18421 validation_1-rmse:0.14979
[43] validation_0-rmse:0.18360 validation_1-rmse:0.14850
[44] validation_0-rmse:0.18275 validation_1-rmse:0.14733
[45] validation_0-rmse:0.18253 validation_1-rmse:0.14597
[46] validation_0-rmse:0.18183 validation_1-rmse:0.14470
[47] validation_0-rmse:0.18111 validation_1-rmse:0.14361
[48] validation_0-rmse:0.18060 validation_1-rmse:0.14243
[49] validation_0-rmse:0.18001 validation_1-rmse:0.14134
[50] validation_0-rmse:0.17953 validation_1-rmse:0.14030
[51] validation_0-rmse:0.17899 validation_1-rmse:0.13927
[52] validation_0-rmse:0.17830 validation_1-rmse:0.13817
[53] validation_0-rmse:0.17770 validation_1-rmse:0.13720
[54] validation_0-rmse:0.17702 validation_1-rmse:0.13629
[55] validation_0-rmse:0.17650 validation_1-rmse:0.13531
[56] validation_0-rmse:0.17625 validation_1-rmse:0.13440
[57] validation_0-rmse:0.17580 validation_1-rmse:0.13352
[58] validation_0-rmse:0.17530 validation_1-rmse:0.13268
[59] validation_0-rmse:0.17486 validation_1-rmse:0.13166
[60] validation_0-rmse:0.17438 validation_1-rmse:0.13071
[61] validation_0-rmse:0.17387 validation_1-rmse:0.12991
[62] validation_0-rmse:0.17356 validation_1-rmse:0.12914
[63] validation_0-rmse:0.17311 validation_1-rmse:0.12839
[64] validation_0-rmse:0.17265 validation_1-rmse:0.12767
[65] validation_0-rmse:0.17209 validation_1-rmse:0.12682
[66] validation_0-rmse:0.17197 validation_1-rmse:0.12595
[67] validation_0-rmse:0.17157 validation_1-rmse:0.12506
[68] validation_0-rmse:0.17131 validation_1-rmse:0.12439
[69] validation_0-rmse:0.17088 validation_1-rmse:0.12371
[70] validation_0-rmse:0.17038 validation_1-rmse:0.12298
[71] validation_0-rmse:0.17009 validation_1-rmse:0.12235
[72] validation_0-rmse:0.16979 validation_1-rmse:0.12172
[73] validation_0-rmse:0.16934 validation_1-rmse:0.12118
[74] validation_0-rmse:0.16902 validation_1-rmse:0.12050
[75] validation_0-rmse:0.16881 validation_1-rmse:0.11988
[76] validation_0-rmse:0.16846 validation_1-rmse:0.11928
[77] validation_0-rmse:0.16809 validation_1-rmse:0.11846
[78] validation_0-rmse:0.16774 validation_1-rmse:0.11791
[79] validation_0-rmse:0.16745 validation_1-rmse:0.11738
[80] validation_0-rmse:0.16717 validation_1-rmse:0.11683
[81] validation_0-rmse:0.16702 validation_1-rmse:0.11599
[82] validation_0-rmse:0.16677 validation_1-rmse:0.11535
[83] validation_0-rmse:0.16649 validation_1-rmse:0.11468
[84] validation_0-rmse:0.16605 validation_1-rmse:0.11415
[85] validation_0-rmse:0.16591 validation_1-rmse:0.11350
[86] validation_0-rmse:0.16560 validation_1-rmse:0.11303
[87] validation_0-rmse:0.16531 validation_1-rmse:0.11259
[88] validation_0-rmse:0.16504 validation_1-rmse:0.11185
[89] validation_0-rmse:0.16485 validation_1-rmse:0.11134
[90] validation_0-rmse:0.16463 validation_1-rmse:0.11083
[91] validation_0-rmse:0.16436 validation_1-rmse:0.11041
[92] validation_0-rmse:0.16412 validation_1-rmse:0.10988
[93] validation_0-rmse:0.16388 validation_1-rmse:0.10942
[94] validation_0-rmse:0.16391 validation_1-rmse:0.10881
[95] validation_0-rmse:0.16357 validation_1-rmse:0.10838
[96] validation_0-rmse:0.16358 validation_1-rmse:0.10796
[97] validation_0-rmse:0.16338 validation_1-rmse:0.10756
[98] validation_0-rmse:0.16339 validation_1-rmse:0.10688
[99] validation_0-rmse:0.16321 validation_1-rmse:0.10649
2025-04-29 01:23:00,451 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.74 secs) --------------------
2025-04-29 01:23:00,452 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:01,085 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-02-20 00:00:00 to 2025-03-22 00:00:00, 9/11 trains
2025-04-29 01:23:01,086 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1742601600_prediction.feather
2025-04-29 01:23:01,094 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:23:01,101 - FreqaiExampleStrategy - INFO - 目标列形状:(52850,)
2025-04-29 01:23:01,103 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.102027
1 0.003285 50.102027
2 0.001898 50.102027
3 0.000484 50.102027
4 0.001688 50.102027
2025-04-29 01:23:01,113 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:23:01,120 - FreqaiExampleStrategy - INFO - 目标列形状:(57650,)
2025-04-29 01:23:01,122 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.079967
1 0.003285 50.079967
2 0.001898 50.079967
3 0.000484 50.079967
4 0.001688 50.079967
2025-04-29 01:23:01,127 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1742601600/cb_btc_1742601600
2025-04-29 01:23:01,128 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:23:01,152 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:01,155 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-02-20 to 2025-03-21 --------------------
2025-04-29 01:23:06,424 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:23:06,425 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.26992 validation_1-rmse:0.26756
[1] validation_0-rmse:0.26551 validation_1-rmse:0.26201
[2] validation_0-rmse:0.26111 validation_1-rmse:0.25656
[3] validation_0-rmse:0.25690 validation_1-rmse:0.25154
[4] validation_0-rmse:0.25291 validation_1-rmse:0.24683
[5] validation_0-rmse:0.24933 validation_1-rmse:0.24228
[6] validation_0-rmse:0.24598 validation_1-rmse:0.23796
[7] validation_0-rmse:0.24252 validation_1-rmse:0.23392
[8] validation_0-rmse:0.23953 validation_1-rmse:0.22978
[9] validation_0-rmse:0.23634 validation_1-rmse:0.22592
[10] validation_0-rmse:0.23330 validation_1-rmse:0.22229
[11] validation_0-rmse:0.23059 validation_1-rmse:0.21875
[12] validation_0-rmse:0.22799 validation_1-rmse:0.21546
[13] validation_0-rmse:0.22565 validation_1-rmse:0.21212
[14] validation_0-rmse:0.22329 validation_1-rmse:0.20904
[15] validation_0-rmse:0.22111 validation_1-rmse:0.20604
[16] validation_0-rmse:0.21894 validation_1-rmse:0.20318
[17] validation_0-rmse:0.21715 validation_1-rmse:0.20021
[18] validation_0-rmse:0.21499 validation_1-rmse:0.19735
[19] validation_0-rmse:0.21283 validation_1-rmse:0.19480
[20] validation_0-rmse:0.21109 validation_1-rmse:0.19209
[21] validation_0-rmse:0.20904 validation_1-rmse:0.18969
[22] validation_0-rmse:0.20762 validation_1-rmse:0.18718
[23] validation_0-rmse:0.20580 validation_1-rmse:0.18498
[24] validation_0-rmse:0.20434 validation_1-rmse:0.18262
[25] validation_0-rmse:0.20267 validation_1-rmse:0.18048
[26] validation_0-rmse:0.20106 validation_1-rmse:0.17844
[27] validation_0-rmse:0.19945 validation_1-rmse:0.17647
[28] validation_0-rmse:0.19813 validation_1-rmse:0.17443
[29] validation_0-rmse:0.19669 validation_1-rmse:0.17264
[30] validation_0-rmse:0.19541 validation_1-rmse:0.17054
[31] validation_0-rmse:0.19401 validation_1-rmse:0.16881
[32] validation_0-rmse:0.19263 validation_1-rmse:0.16719
[33] validation_0-rmse:0.19134 validation_1-rmse:0.16560
[34] validation_0-rmse:0.18996 validation_1-rmse:0.16365
[35] validation_0-rmse:0.18864 validation_1-rmse:0.16211
[36] validation_0-rmse:0.18752 validation_1-rmse:0.16069
[37] validation_0-rmse:0.18652 validation_1-rmse:0.15898
[38] validation_0-rmse:0.18540 validation_1-rmse:0.15751
[39] validation_0-rmse:0.18429 validation_1-rmse:0.15616
[40] validation_0-rmse:0.18317 validation_1-rmse:0.15475
[41] validation_0-rmse:0.18215 validation_1-rmse:0.15324
[42] validation_0-rmse:0.18119 validation_1-rmse:0.15199
[43] validation_0-rmse:0.18008 validation_1-rmse:0.15057
[44] validation_0-rmse:0.17926 validation_1-rmse:0.14942
[45] validation_0-rmse:0.17841 validation_1-rmse:0.14813
[46] validation_0-rmse:0.17755 validation_1-rmse:0.14700
[47] validation_0-rmse:0.17672 validation_1-rmse:0.14572
[48] validation_0-rmse:0.17586 validation_1-rmse:0.14466
[49] validation_0-rmse:0.17511 validation_1-rmse:0.14354
[50] validation_0-rmse:0.17440 validation_1-rmse:0.14236
[51] validation_0-rmse:0.17354 validation_1-rmse:0.14130
[52] validation_0-rmse:0.17281 validation_1-rmse:0.14035
[53] validation_0-rmse:0.17210 validation_1-rmse:0.13942
[54] validation_0-rmse:0.17136 validation_1-rmse:0.13843
[55] validation_0-rmse:0.17045 validation_1-rmse:0.13715
[56] validation_0-rmse:0.16971 validation_1-rmse:0.13629
[57] validation_0-rmse:0.16900 validation_1-rmse:0.13511
[58] validation_0-rmse:0.16834 validation_1-rmse:0.13426
[59] validation_0-rmse:0.16763 validation_1-rmse:0.13323
[60] validation_0-rmse:0.16702 validation_1-rmse:0.13242
[61] validation_0-rmse:0.16639 validation_1-rmse:0.13164
[62] validation_0-rmse:0.16586 validation_1-rmse:0.13079
[63] validation_0-rmse:0.16527 validation_1-rmse:0.13006
[64] validation_0-rmse:0.16458 validation_1-rmse:0.12914
[65] validation_0-rmse:0.16396 validation_1-rmse:0.12841
[66] validation_0-rmse:0.16332 validation_1-rmse:0.12742
[67] validation_0-rmse:0.16290 validation_1-rmse:0.12665
[68] validation_0-rmse:0.16248 validation_1-rmse:0.12584
[69] validation_0-rmse:0.16192 validation_1-rmse:0.12503
[70] validation_0-rmse:0.16128 validation_1-rmse:0.12435
[71] validation_0-rmse:0.16078 validation_1-rmse:0.12371
[72] validation_0-rmse:0.16032 validation_1-rmse:0.12311
[73] validation_0-rmse:0.15998 validation_1-rmse:0.12241
[74] validation_0-rmse:0.15959 validation_1-rmse:0.12184
[75] validation_0-rmse:0.15922 validation_1-rmse:0.12121
[76] validation_0-rmse:0.15877 validation_1-rmse:0.12064
[77] validation_0-rmse:0.15830 validation_1-rmse:0.11981
[78] validation_0-rmse:0.15791 validation_1-rmse:0.11927
[79] validation_0-rmse:0.15751 validation_1-rmse:0.11859
[80] validation_0-rmse:0.15716 validation_1-rmse:0.11795
[81] validation_0-rmse:0.15680 validation_1-rmse:0.11740
[82] validation_0-rmse:0.15624 validation_1-rmse:0.11683
[83] validation_0-rmse:0.15578 validation_1-rmse:0.11632
[84] validation_0-rmse:0.15553 validation_1-rmse:0.11586
[85] validation_0-rmse:0.15471 validation_1-rmse:0.11513
[86] validation_0-rmse:0.15444 validation_1-rmse:0.11465
[87] validation_0-rmse:0.15417 validation_1-rmse:0.11406
[88] validation_0-rmse:0.15387 validation_1-rmse:0.11359
[89] validation_0-rmse:0.15359 validation_1-rmse:0.11319
[90] validation_0-rmse:0.15332 validation_1-rmse:0.11269
[91] validation_0-rmse:0.15301 validation_1-rmse:0.11221
[92] validation_0-rmse:0.15258 validation_1-rmse:0.11176
[93] validation_0-rmse:0.15231 validation_1-rmse:0.11135
[94] validation_0-rmse:0.15202 validation_1-rmse:0.11093
[95] validation_0-rmse:0.15185 validation_1-rmse:0.11041
[96] validation_0-rmse:0.15173 validation_1-rmse:0.11000
[97] validation_0-rmse:0.15150 validation_1-rmse:0.10961
[98] validation_0-rmse:0.15114 validation_1-rmse:0.10917
[99] validation_0-rmse:0.15096 validation_1-rmse:0.10882
2025-04-29 01:23:07,093 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.96 secs) --------------------
2025-04-29 01:23:07,094 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:07,615 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-03-02 00:00:00 to 2025-04-01 00:00:00, 10/11 trains
2025-04-29 01:23:07,615 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1743465600_prediction.feather
2025-04-29 01:23:07,624 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:23:07,631 - FreqaiExampleStrategy - INFO - 目标列形状:(57650,)
2025-04-29 01:23:07,633 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.079967
1 0.003285 50.079967
2 0.001898 50.079967
3 0.000484 50.079967
4 0.001688 50.079967
2025-04-29 01:23:07,640 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:23:07,647 - FreqaiExampleStrategy - INFO - 目标列形状:(62450,)
2025-04-29 01:23:07,649 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.024153
1 0.003285 50.024153
2 0.001898 50.024153
3 0.000484 50.024153
4 0.001688 50.024153
2025-04-29 01:23:07,654 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1743465600/cb_btc_1743465600
2025-04-29 01:23:07,654 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:23:07,670 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:07,671 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-03-02 to 2025-03-31 --------------------
2025-04-29 01:23:12,541 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:23:12,541 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.28468 validation_1-rmse:0.28491
[1] validation_0-rmse:0.27961 validation_1-rmse:0.27914
[2] validation_0-rmse:0.27524 validation_1-rmse:0.27370
[3] validation_0-rmse:0.27054 validation_1-rmse:0.26858
[4] validation_0-rmse:0.26601 validation_1-rmse:0.26362
[5] validation_0-rmse:0.26219 validation_1-rmse:0.25896
[6] validation_0-rmse:0.25814 validation_1-rmse:0.25450
[7] validation_0-rmse:0.25500 validation_1-rmse:0.25026
[8] validation_0-rmse:0.25145 validation_1-rmse:0.24602
[9] validation_0-rmse:0.24843 validation_1-rmse:0.24213
[10] validation_0-rmse:0.24527 validation_1-rmse:0.23824
[11] validation_0-rmse:0.24238 validation_1-rmse:0.23440
[12] validation_0-rmse:0.23940 validation_1-rmse:0.23096
[13] validation_0-rmse:0.23630 validation_1-rmse:0.22764
[14] validation_0-rmse:0.23385 validation_1-rmse:0.22440
[15] validation_0-rmse:0.23099 validation_1-rmse:0.22128
[16] validation_0-rmse:0.22865 validation_1-rmse:0.21801
[17] validation_0-rmse:0.22620 validation_1-rmse:0.21515
[18] validation_0-rmse:0.22375 validation_1-rmse:0.21210
[19] validation_0-rmse:0.22142 validation_1-rmse:0.20925
[20] validation_0-rmse:0.21927 validation_1-rmse:0.20663
[21] validation_0-rmse:0.21720 validation_1-rmse:0.20416
[22] validation_0-rmse:0.21528 validation_1-rmse:0.20170
[23] validation_0-rmse:0.21330 validation_1-rmse:0.19913
[24] validation_0-rmse:0.21136 validation_1-rmse:0.19693
[25] validation_0-rmse:0.21002 validation_1-rmse:0.19438
[26] validation_0-rmse:0.20807 validation_1-rmse:0.19222
[27] validation_0-rmse:0.20636 validation_1-rmse:0.19016
[28] validation_0-rmse:0.20439 validation_1-rmse:0.18763
[29] validation_0-rmse:0.20276 validation_1-rmse:0.18559
[30] validation_0-rmse:0.20114 validation_1-rmse:0.18380
[31] validation_0-rmse:0.19965 validation_1-rmse:0.18163
[32] validation_0-rmse:0.19833 validation_1-rmse:0.17955
[33] validation_0-rmse:0.19688 validation_1-rmse:0.17782
[34] validation_0-rmse:0.19558 validation_1-rmse:0.17614
[35] validation_0-rmse:0.19420 validation_1-rmse:0.17451
[36] validation_0-rmse:0.19297 validation_1-rmse:0.17293
[37] validation_0-rmse:0.19169 validation_1-rmse:0.17111
[38] validation_0-rmse:0.19038 validation_1-rmse:0.16943
[39] validation_0-rmse:0.18941 validation_1-rmse:0.16798
[40] validation_0-rmse:0.18828 validation_1-rmse:0.16657
[41] validation_0-rmse:0.18724 validation_1-rmse:0.16485
[42] validation_0-rmse:0.18620 validation_1-rmse:0.16347
[43] validation_0-rmse:0.18525 validation_1-rmse:0.16204
[44] validation_0-rmse:0.18429 validation_1-rmse:0.16073
[45] validation_0-rmse:0.18324 validation_1-rmse:0.15951
[46] validation_0-rmse:0.18250 validation_1-rmse:0.15797
[47] validation_0-rmse:0.18157 validation_1-rmse:0.15682
[48] validation_0-rmse:0.18069 validation_1-rmse:0.15566
[49] validation_0-rmse:0.18002 validation_1-rmse:0.15440
[50] validation_0-rmse:0.17914 validation_1-rmse:0.15322
[51] validation_0-rmse:0.17842 validation_1-rmse:0.15220
[52] validation_0-rmse:0.17756 validation_1-rmse:0.15107
[53] validation_0-rmse:0.17668 validation_1-rmse:0.15007
[54] validation_0-rmse:0.17596 validation_1-rmse:0.14866
[55] validation_0-rmse:0.17525 validation_1-rmse:0.14775
[56] validation_0-rmse:0.17467 validation_1-rmse:0.14653
[57] validation_0-rmse:0.17390 validation_1-rmse:0.14564
[58] validation_0-rmse:0.17326 validation_1-rmse:0.14478
[59] validation_0-rmse:0.17273 validation_1-rmse:0.14356
[60] validation_0-rmse:0.17218 validation_1-rmse:0.14269
[61] validation_0-rmse:0.17157 validation_1-rmse:0.14186
[62] validation_0-rmse:0.17120 validation_1-rmse:0.14083
[63] validation_0-rmse:0.17069 validation_1-rmse:0.14002
[64] validation_0-rmse:0.17012 validation_1-rmse:0.13912
[65] validation_0-rmse:0.16942 validation_1-rmse:0.13834
[66] validation_0-rmse:0.16914 validation_1-rmse:0.13720
[67] validation_0-rmse:0.16856 validation_1-rmse:0.13648
[68] validation_0-rmse:0.16800 validation_1-rmse:0.13569
[69] validation_0-rmse:0.16796 validation_1-rmse:0.13472
[70] validation_0-rmse:0.16737 validation_1-rmse:0.13405
[71] validation_0-rmse:0.16686 validation_1-rmse:0.13342
[72] validation_0-rmse:0.16639 validation_1-rmse:0.13270
[73] validation_0-rmse:0.16648 validation_1-rmse:0.13149
[74] validation_0-rmse:0.16609 validation_1-rmse:0.13086
[75] validation_0-rmse:0.16560 validation_1-rmse:0.13025
[76] validation_0-rmse:0.16530 validation_1-rmse:0.12925
[77] validation_0-rmse:0.16492 validation_1-rmse:0.12824
[78] validation_0-rmse:0.16451 validation_1-rmse:0.12770
[79] validation_0-rmse:0.16414 validation_1-rmse:0.12710
[80] validation_0-rmse:0.16377 validation_1-rmse:0.12654
[81] validation_0-rmse:0.16338 validation_1-rmse:0.12595
[82] validation_0-rmse:0.16317 validation_1-rmse:0.12490
[83] validation_0-rmse:0.16249 validation_1-rmse:0.12361
[84] validation_0-rmse:0.16217 validation_1-rmse:0.12307
[85] validation_0-rmse:0.16178 validation_1-rmse:0.12255
[86] validation_0-rmse:0.16149 validation_1-rmse:0.12206
[87] validation_0-rmse:0.16113 validation_1-rmse:0.12155
[88] validation_0-rmse:0.16049 validation_1-rmse:0.12061
[89] validation_0-rmse:0.16008 validation_1-rmse:0.11990
[90] validation_0-rmse:0.15955 validation_1-rmse:0.11882
[91] validation_0-rmse:0.15927 validation_1-rmse:0.11842
[92] validation_0-rmse:0.15891 validation_1-rmse:0.11796
[93] validation_0-rmse:0.15880 validation_1-rmse:0.11730
[94] validation_0-rmse:0.15829 validation_1-rmse:0.11631
[95] validation_0-rmse:0.15809 validation_1-rmse:0.11584
[96] validation_0-rmse:0.15778 validation_1-rmse:0.11544
[97] validation_0-rmse:0.15763 validation_1-rmse:0.11504
[98] validation_0-rmse:0.15724 validation_1-rmse:0.11438
[99] validation_0-rmse:0.15694 validation_1-rmse:0.11396
2025-04-29 01:23:13,172 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.52 secs) --------------------
2025-04-29 01:23:13,173 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:13,698 - freqtrade.freqai.freqai_interface - INFO - Training BTC/USDT, 1/2 pairs from 2025-03-12 00:00:00 to 2025-04-11 00:00:00, 11/11 trains
2025-04-29 01:23:13,699 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_btc_1744329600_prediction.feather
2025-04-29 01:23:13,709 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:23:13,717 - FreqaiExampleStrategy - INFO - 目标列形状:(62450,)
2025-04-29 01:23:13,719 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.024153
1 0.003285 50.024153
2 0.001898 50.024153
3 0.000484 50.024153
4 0.001688 50.024153
2025-04-29 01:23:13,729 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对BTC/USDT
2025-04-29 01:23:13,736 - FreqaiExampleStrategy - INFO - 目标列形状:(66770,)
2025-04-29 01:23:13,738 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.003572 50.093162
1 0.003285 50.093162
2 0.001898 50.093162
3 0.000484 50.093162
4 0.001688 50.093162
2025-04-29 01:23:13,742 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-BTC_1744329600/cb_btc_1744329600
2025-04-29 01:23:13,743 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training BTC/USDT --------------------
2025-04-29 01:23:13,761 - freqtrade.freqai.data_kitchen - INFO - BTC/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:13,761 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-03-12 to 2025-04-10 --------------------
2025-04-29 01:23:18,729 - datasieve.pipeline - INFO - DI tossed 2001 predictions for being too far from training data.
2025-04-29 01:23:18,732 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 75 features
2025-04-29 01:23:18,732 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.32950 validation_1-rmse:0.29220
[1] validation_0-rmse:0.32402 validation_1-rmse:0.28580
[2] validation_0-rmse:0.31922 validation_1-rmse:0.27974
[3] validation_0-rmse:0.31450 validation_1-rmse:0.27409
[4] validation_0-rmse:0.30969 validation_1-rmse:0.26866
[5] validation_0-rmse:0.30585 validation_1-rmse:0.26346
[6] validation_0-rmse:0.30202 validation_1-rmse:0.25855
[7] validation_0-rmse:0.29888 validation_1-rmse:0.25375
[8] validation_0-rmse:0.29520 validation_1-rmse:0.24919
[9] validation_0-rmse:0.29164 validation_1-rmse:0.24487
[10] validation_0-rmse:0.28843 validation_1-rmse:0.24072
[11] validation_0-rmse:0.28514 validation_1-rmse:0.23667
[12] validation_0-rmse:0.28114 validation_1-rmse:0.23279
[13] validation_0-rmse:0.27740 validation_1-rmse:0.22909
[14] validation_0-rmse:0.27421 validation_1-rmse:0.22543
[15] validation_0-rmse:0.27115 validation_1-rmse:0.22210
[16] validation_0-rmse:0.26820 validation_1-rmse:0.21859
[17] validation_0-rmse:0.26549 validation_1-rmse:0.21528
[18] validation_0-rmse:0.26254 validation_1-rmse:0.21226
[19] validation_0-rmse:0.25967 validation_1-rmse:0.20927
[20] validation_0-rmse:0.25735 validation_1-rmse:0.20641
[21] validation_0-rmse:0.25470 validation_1-rmse:0.20366
[22] validation_0-rmse:0.25265 validation_1-rmse:0.20073
[23] validation_0-rmse:0.25054 validation_1-rmse:0.19819
[24] validation_0-rmse:0.24806 validation_1-rmse:0.19573
[25] validation_0-rmse:0.24570 validation_1-rmse:0.19304
[26] validation_0-rmse:0.24361 validation_1-rmse:0.19076
[27] validation_0-rmse:0.24148 validation_1-rmse:0.18853
[28] validation_0-rmse:0.24014 validation_1-rmse:0.18621
[29] validation_0-rmse:0.23792 validation_1-rmse:0.18410
[30] validation_0-rmse:0.23603 validation_1-rmse:0.18203
[31] validation_0-rmse:0.23421 validation_1-rmse:0.17990
[32] validation_0-rmse:0.23264 validation_1-rmse:0.17800
[33] validation_0-rmse:0.23087 validation_1-rmse:0.17616
[34] validation_0-rmse:0.22949 validation_1-rmse:0.17427
[35] validation_0-rmse:0.22857 validation_1-rmse:0.17234
[36] validation_0-rmse:0.22690 validation_1-rmse:0.17065
[37] validation_0-rmse:0.22566 validation_1-rmse:0.16898
[38] validation_0-rmse:0.22462 validation_1-rmse:0.16738
[39] validation_0-rmse:0.22376 validation_1-rmse:0.16567
[40] validation_0-rmse:0.22232 validation_1-rmse:0.16410
[41] validation_0-rmse:0.22105 validation_1-rmse:0.16265
[42] validation_0-rmse:0.22006 validation_1-rmse:0.16111
[43] validation_0-rmse:0.21847 validation_1-rmse:0.15976
[44] validation_0-rmse:0.21782 validation_1-rmse:0.15824
[45] validation_0-rmse:0.21641 validation_1-rmse:0.15686
[46] validation_0-rmse:0.21552 validation_1-rmse:0.15554
[47] validation_0-rmse:0.21459 validation_1-rmse:0.15417
[48] validation_0-rmse:0.21339 validation_1-rmse:0.15293
[49] validation_0-rmse:0.21255 validation_1-rmse:0.15176
[50] validation_0-rmse:0.21192 validation_1-rmse:0.15047
[51] validation_0-rmse:0.21115 validation_1-rmse:0.14910
[52] validation_0-rmse:0.21072 validation_1-rmse:0.14774
[53] validation_0-rmse:0.20992 validation_1-rmse:0.14670
[54] validation_0-rmse:0.20839 validation_1-rmse:0.14541
[55] validation_0-rmse:0.20753 validation_1-rmse:0.14442
[56] validation_0-rmse:0.20648 validation_1-rmse:0.14328
[57] validation_0-rmse:0.20564 validation_1-rmse:0.14229
[58] validation_0-rmse:0.20473 validation_1-rmse:0.14137
[59] validation_0-rmse:0.20418 validation_1-rmse:0.14011
[60] validation_0-rmse:0.20341 validation_1-rmse:0.13923
[61] validation_0-rmse:0.20258 validation_1-rmse:0.13839
[62] validation_0-rmse:0.20230 validation_1-rmse:0.13723
[63] validation_0-rmse:0.20075 validation_1-rmse:0.13546
[64] validation_0-rmse:0.20007 validation_1-rmse:0.13467
[65] validation_0-rmse:0.19937 validation_1-rmse:0.13387
[66] validation_0-rmse:0.19875 validation_1-rmse:0.13296
[67] validation_0-rmse:0.19709 validation_1-rmse:0.13137
[68] validation_0-rmse:0.19675 validation_1-rmse:0.13042
[69] validation_0-rmse:0.19617 validation_1-rmse:0.12968
[70] validation_0-rmse:0.19560 validation_1-rmse:0.12900
[71] validation_0-rmse:0.19492 validation_1-rmse:0.12834
[72] validation_0-rmse:0.19319 validation_1-rmse:0.12681
[73] validation_0-rmse:0.19272 validation_1-rmse:0.12612
[74] validation_0-rmse:0.19230 validation_1-rmse:0.12535
[75] validation_0-rmse:0.19170 validation_1-rmse:0.12474
[76] validation_0-rmse:0.19058 validation_1-rmse:0.12338
[77] validation_0-rmse:0.19010 validation_1-rmse:0.12279
[78] validation_0-rmse:0.18961 validation_1-rmse:0.12223
[79] validation_0-rmse:0.18960 validation_1-rmse:0.12156
[80] validation_0-rmse:0.18882 validation_1-rmse:0.12038
[81] validation_0-rmse:0.18819 validation_1-rmse:0.11975
[82] validation_0-rmse:0.18789 validation_1-rmse:0.11916
[83] validation_0-rmse:0.18738 validation_1-rmse:0.11864
[84] validation_0-rmse:0.18718 validation_1-rmse:0.11801
[85] validation_0-rmse:0.18600 validation_1-rmse:0.11698
[86] validation_0-rmse:0.18572 validation_1-rmse:0.11653
[87] validation_0-rmse:0.18534 validation_1-rmse:0.11603
[88] validation_0-rmse:0.18478 validation_1-rmse:0.11508
[89] validation_0-rmse:0.18430 validation_1-rmse:0.11459
[90] validation_0-rmse:0.18447 validation_1-rmse:0.11396
[91] validation_0-rmse:0.18424 validation_1-rmse:0.11352
[92] validation_0-rmse:0.18367 validation_1-rmse:0.11307
[93] validation_0-rmse:0.18333 validation_1-rmse:0.11265
[94] validation_0-rmse:0.18313 validation_1-rmse:0.11216
[95] validation_0-rmse:0.18275 validation_1-rmse:0.11157
[96] validation_0-rmse:0.18275 validation_1-rmse:0.11106
[97] validation_0-rmse:0.18248 validation_1-rmse:0.11068
[98] validation_0-rmse:0.18220 validation_1-rmse:0.11033
[99] validation_0-rmse:0.18198 validation_1-rmse:0.10994
2025-04-29 01:23:19,380 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training BTC/USDT (5.64 secs) --------------------
2025-04-29 01:23:19,381 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:19,963 - FreqaiExampleStrategy - INFO - 动态参数buy_rsi=39.26145316407591, sell_rsi=59.26145316407591, stoploss=-0.15, trailing_stop_positive=0.05
2025-04-29 01:23:19,984 - FreqaiExampleStrategy - INFO - up_or_down 值统计:
up_or_down
1 33535
0 33236
2025-04-29 01:23:19,985 - FreqaiExampleStrategy - INFO - do_predict 值统计:
do_predict
0.0 35773
1.0 30998
2025-04-29 01:23:19,989 - FreqaiExampleStrategy - INFO - 处理交易对SOL/USDT
2025-04-29 01:23:19,991 - freqtrade.freqai.freqai_interface - INFO - Training 11 timeranges
2025-04-29 01:23:19,992 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2024-12-02 00:00:00 to 2025-01-01 00:00:00, 1/11 trains
2025-04-29 01:23:19,992 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1735689600_prediction.feather
2025-04-29 01:23:20,046 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 5m to 8690
2025-04-29 01:23:20,047 - freqtrade.data.dataprovider - INFO - Loading data for SOL/USDT 5m from 2024-12-01 19:50:00 to 2025-04-20 00:00:00
2025-04-29 01:23:20,147 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 1h to 770
2025-04-29 01:23:20,148 - freqtrade.data.dataprovider - INFO - Loading data for SOL/USDT 1h from 2024-11-29 22:00:00 to 2025-04-20 00:00:00
2025-04-29 01:23:20,246 - freqtrade.data.dataprovider - INFO - Increasing startup_candle_count for freqai on 3m to 14450
2025-04-29 01:23:20,247 - freqtrade.data.dataprovider - INFO - Loading data for BTC/USDT 3m from 2024-12-01 21:30:00 to 2025-04-20 00:00:00
2025-04-29 01:23:20,775 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:20,780 - FreqaiExampleStrategy - INFO - 目标列形状:(14450,)
2025-04-29 01:23:20,781 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.58814
1 0.003044 49.58814
2 0.000465 49.58814
3 -0.000380 49.58814
4 0.002829 49.58814
2025-04-29 01:23:20,785 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:20,790 - FreqaiExampleStrategy - INFO - 目标列形状:(19250,)
2025-04-29 01:23:20,792 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.68088
1 0.003044 49.68088
2 0.000465 49.68088
3 -0.000380 49.68088
4 0.002829 49.68088
2025-04-29 01:23:20,799 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1735689600/cb_sol_1735689600
2025-04-29 01:23:20,799 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:23:20,829 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:20,830 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2024-12-02 to 2024-12-31 --------------------
2025-04-29 01:23:25,946 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 111 features
2025-04-29 01:23:25,947 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.30164 validation_1-rmse:0.29585
[1] validation_0-rmse:0.29609 validation_1-rmse:0.28921
[2] validation_0-rmse:0.29103 validation_1-rmse:0.28298
[3] validation_0-rmse:0.28604 validation_1-rmse:0.27706
[4] validation_0-rmse:0.28108 validation_1-rmse:0.27129
[5] validation_0-rmse:0.27670 validation_1-rmse:0.26609
[6] validation_0-rmse:0.27234 validation_1-rmse:0.26092
[7] validation_0-rmse:0.26874 validation_1-rmse:0.25593
[8] validation_0-rmse:0.26461 validation_1-rmse:0.25118
[9] validation_0-rmse:0.26074 validation_1-rmse:0.24677
[10] validation_0-rmse:0.25745 validation_1-rmse:0.24239
[11] validation_0-rmse:0.25460 validation_1-rmse:0.23832
[12] validation_0-rmse:0.25121 validation_1-rmse:0.23441
[13] validation_0-rmse:0.24825 validation_1-rmse:0.23068
[14] validation_0-rmse:0.24580 validation_1-rmse:0.22694
[15] validation_0-rmse:0.24286 validation_1-rmse:0.22346
[16] validation_0-rmse:0.24051 validation_1-rmse:0.22006
[17] validation_0-rmse:0.23821 validation_1-rmse:0.21690
[18] validation_0-rmse:0.23549 validation_1-rmse:0.21383
[19] validation_0-rmse:0.23335 validation_1-rmse:0.21087
[20] validation_0-rmse:0.23089 validation_1-rmse:0.20804
[21] validation_0-rmse:0.22918 validation_1-rmse:0.20505
[22] validation_0-rmse:0.22716 validation_1-rmse:0.20240
[23] validation_0-rmse:0.22562 validation_1-rmse:0.19981
[24] validation_0-rmse:0.22385 validation_1-rmse:0.19723
[25] validation_0-rmse:0.22201 validation_1-rmse:0.19473
[26] validation_0-rmse:0.22016 validation_1-rmse:0.19245
[27] validation_0-rmse:0.21834 validation_1-rmse:0.19024
[28] validation_0-rmse:0.21671 validation_1-rmse:0.18789
[29] validation_0-rmse:0.21493 validation_1-rmse:0.18579
[30] validation_0-rmse:0.21385 validation_1-rmse:0.18351
[31] validation_0-rmse:0.21216 validation_1-rmse:0.18156
[32] validation_0-rmse:0.21088 validation_1-rmse:0.17941
[33] validation_0-rmse:0.20953 validation_1-rmse:0.17754
[34] validation_0-rmse:0.20805 validation_1-rmse:0.17575
[35] validation_0-rmse:0.20648 validation_1-rmse:0.17399
[36] validation_0-rmse:0.20515 validation_1-rmse:0.17220
[37] validation_0-rmse:0.20382 validation_1-rmse:0.17031
[38] validation_0-rmse:0.20257 validation_1-rmse:0.16871
[39] validation_0-rmse:0.20125 validation_1-rmse:0.16718
[40] validation_0-rmse:0.20005 validation_1-rmse:0.16574
[41] validation_0-rmse:0.19885 validation_1-rmse:0.16415
[42] validation_0-rmse:0.19789 validation_1-rmse:0.16270
[43] validation_0-rmse:0.19680 validation_1-rmse:0.16130
[44] validation_0-rmse:0.19564 validation_1-rmse:0.15993
[45] validation_0-rmse:0.19480 validation_1-rmse:0.15854
[46] validation_0-rmse:0.19376 validation_1-rmse:0.15728
[47] validation_0-rmse:0.19290 validation_1-rmse:0.15568
[48] validation_0-rmse:0.19223 validation_1-rmse:0.15445
[49] validation_0-rmse:0.19129 validation_1-rmse:0.15330
[50] validation_0-rmse:0.19035 validation_1-rmse:0.15194
[51] validation_0-rmse:0.18948 validation_1-rmse:0.15082
[52] validation_0-rmse:0.18882 validation_1-rmse:0.14945
[53] validation_0-rmse:0.18801 validation_1-rmse:0.14840
[54] validation_0-rmse:0.18707 validation_1-rmse:0.14736
[55] validation_0-rmse:0.18637 validation_1-rmse:0.14635
[56] validation_0-rmse:0.18571 validation_1-rmse:0.14542
[57] validation_0-rmse:0.18497 validation_1-rmse:0.14413
[58] validation_0-rmse:0.18443 validation_1-rmse:0.14297
[59] validation_0-rmse:0.18375 validation_1-rmse:0.14203
[60] validation_0-rmse:0.18319 validation_1-rmse:0.14111
[61] validation_0-rmse:0.18266 validation_1-rmse:0.14030
[62] validation_0-rmse:0.18185 validation_1-rmse:0.13914
[63] validation_0-rmse:0.18145 validation_1-rmse:0.13831
[64] validation_0-rmse:0.18135 validation_1-rmse:0.13720
[65] validation_0-rmse:0.18075 validation_1-rmse:0.13643
[66] validation_0-rmse:0.18020 validation_1-rmse:0.13560
[67] validation_0-rmse:0.17951 validation_1-rmse:0.13485
[68] validation_0-rmse:0.17888 validation_1-rmse:0.13414
[69] validation_0-rmse:0.17850 validation_1-rmse:0.13343
[70] validation_0-rmse:0.17798 validation_1-rmse:0.13224
[71] validation_0-rmse:0.17751 validation_1-rmse:0.13133
[72] validation_0-rmse:0.17711 validation_1-rmse:0.13062
[73] validation_0-rmse:0.17701 validation_1-rmse:0.12966
[74] validation_0-rmse:0.17648 validation_1-rmse:0.12872
[75] validation_0-rmse:0.17611 validation_1-rmse:0.12806
[76] validation_0-rmse:0.17573 validation_1-rmse:0.12732
[77] validation_0-rmse:0.17528 validation_1-rmse:0.12664
[78] validation_0-rmse:0.17478 validation_1-rmse:0.12605
[79] validation_0-rmse:0.17432 validation_1-rmse:0.12518
[80] validation_0-rmse:0.17391 validation_1-rmse:0.12466
[81] validation_0-rmse:0.17358 validation_1-rmse:0.12398
[82] validation_0-rmse:0.17315 validation_1-rmse:0.12342
[83] validation_0-rmse:0.17260 validation_1-rmse:0.12276
[84] validation_0-rmse:0.17220 validation_1-rmse:0.12222
[85] validation_0-rmse:0.17182 validation_1-rmse:0.12176
[86] validation_0-rmse:0.17152 validation_1-rmse:0.12124
[87] validation_0-rmse:0.17103 validation_1-rmse:0.12046
[88] validation_0-rmse:0.17085 validation_1-rmse:0.11974
[89] validation_0-rmse:0.17053 validation_1-rmse:0.11930
[90] validation_0-rmse:0.17018 validation_1-rmse:0.11888
[91] validation_0-rmse:0.17011 validation_1-rmse:0.11810
[92] validation_0-rmse:0.16980 validation_1-rmse:0.11762
[93] validation_0-rmse:0.16956 validation_1-rmse:0.11689
[94] validation_0-rmse:0.16923 validation_1-rmse:0.11641
[95] validation_0-rmse:0.16912 validation_1-rmse:0.11579
[96] validation_0-rmse:0.16878 validation_1-rmse:0.11530
[97] validation_0-rmse:0.16857 validation_1-rmse:0.11489
[98] validation_0-rmse:0.16824 validation_1-rmse:0.11442
[99] validation_0-rmse:0.16824 validation_1-rmse:0.11403
2025-04-29 01:23:27,063 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training SOL/USDT (6.26 secs) --------------------
2025-04-29 01:23:27,064 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:27,614 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2024-12-12 00:00:00 to 2025-01-11 00:00:00, 2/11 trains
2025-04-29 01:23:27,614 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1736553600_prediction.feather
2025-04-29 01:23:27,618 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:27,624 - FreqaiExampleStrategy - INFO - 目标列形状:(19250,)
2025-04-29 01:23:27,625 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.68088
1 0.003044 49.68088
2 0.000465 49.68088
3 -0.000380 49.68088
4 0.002829 49.68088
2025-04-29 01:23:27,630 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:27,636 - FreqaiExampleStrategy - INFO - 目标列形状:(24050,)
2025-04-29 01:23:27,638 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.97721
1 0.003044 49.97721
2 0.000465 49.97721
3 -0.000380 49.97721
4 0.002829 49.97721
2025-04-29 01:23:27,643 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1736553600/cb_sol_1736553600
2025-04-29 01:23:27,644 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:23:27,670 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:27,671 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2024-12-12 to 2025-01-10 --------------------
2025-04-29 01:23:32,840 - datasieve.pipeline - INFO - DI tossed 5 predictions for being too far from training data.
2025-04-29 01:23:32,844 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 111 features
2025-04-29 01:23:32,844 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.29597 validation_1-rmse:0.29016
[1] validation_0-rmse:0.29075 validation_1-rmse:0.28391
[2] validation_0-rmse:0.28602 validation_1-rmse:0.27798
[3] validation_0-rmse:0.28062 validation_1-rmse:0.27213
[4] validation_0-rmse:0.27647 validation_1-rmse:0.26682
[5] validation_0-rmse:0.27188 validation_1-rmse:0.26144
[6] validation_0-rmse:0.26781 validation_1-rmse:0.25655
[7] validation_0-rmse:0.26412 validation_1-rmse:0.25180
[8] validation_0-rmse:0.25994 validation_1-rmse:0.24709
[9] validation_0-rmse:0.25649 validation_1-rmse:0.24277
[10] validation_0-rmse:0.25332 validation_1-rmse:0.23850
[11] validation_0-rmse:0.24999 validation_1-rmse:0.23452
[12] validation_0-rmse:0.24687 validation_1-rmse:0.23072
[13] validation_0-rmse:0.24432 validation_1-rmse:0.22694
[14] validation_0-rmse:0.24128 validation_1-rmse:0.22341
[15] validation_0-rmse:0.23869 validation_1-rmse:0.21969
[16] validation_0-rmse:0.23628 validation_1-rmse:0.21635
[17] validation_0-rmse:0.23354 validation_1-rmse:0.21326
[18] validation_0-rmse:0.23123 validation_1-rmse:0.21007
[19] validation_0-rmse:0.22919 validation_1-rmse:0.20707
[20] validation_0-rmse:0.22705 validation_1-rmse:0.20418
[21] validation_0-rmse:0.22505 validation_1-rmse:0.20149
[22] validation_0-rmse:0.22285 validation_1-rmse:0.19887
[23] validation_0-rmse:0.22084 validation_1-rmse:0.19631
[24] validation_0-rmse:0.21877 validation_1-rmse:0.19389
[25] validation_0-rmse:0.21748 validation_1-rmse:0.19133
[26] validation_0-rmse:0.21557 validation_1-rmse:0.18870
[27] validation_0-rmse:0.21374 validation_1-rmse:0.18648
[28] validation_0-rmse:0.21183 validation_1-rmse:0.18432
[29] validation_0-rmse:0.21047 validation_1-rmse:0.18209
[30] validation_0-rmse:0.20873 validation_1-rmse:0.17990
[31] validation_0-rmse:0.20717 validation_1-rmse:0.17795
[32] validation_0-rmse:0.20564 validation_1-rmse:0.17599
[33] validation_0-rmse:0.20428 validation_1-rmse:0.17421
[34] validation_0-rmse:0.20290 validation_1-rmse:0.17229
[35] validation_0-rmse:0.20161 validation_1-rmse:0.17047
[36] validation_0-rmse:0.20018 validation_1-rmse:0.16878
[37] validation_0-rmse:0.19923 validation_1-rmse:0.16688
[38] validation_0-rmse:0.19796 validation_1-rmse:0.16534
[39] validation_0-rmse:0.19668 validation_1-rmse:0.16355
[40] validation_0-rmse:0.19543 validation_1-rmse:0.16204
[41] validation_0-rmse:0.19441 validation_1-rmse:0.16062
[42] validation_0-rmse:0.19344 validation_1-rmse:0.15910
[43] validation_0-rmse:0.19256 validation_1-rmse:0.15759
[44] validation_0-rmse:0.19154 validation_1-rmse:0.15625
[45] validation_0-rmse:0.19048 validation_1-rmse:0.15494
[46] validation_0-rmse:0.18937 validation_1-rmse:0.15366
[47] validation_0-rmse:0.18865 validation_1-rmse:0.15236
[48] validation_0-rmse:0.18784 validation_1-rmse:0.15112
[49] validation_0-rmse:0.18704 validation_1-rmse:0.14998
[50] validation_0-rmse:0.18625 validation_1-rmse:0.14874
[51] validation_0-rmse:0.18541 validation_1-rmse:0.14763
[52] validation_0-rmse:0.18456 validation_1-rmse:0.14659
[53] validation_0-rmse:0.18383 validation_1-rmse:0.14530
[54] validation_0-rmse:0.18315 validation_1-rmse:0.14420
[55] validation_0-rmse:0.18234 validation_1-rmse:0.14321
[56] validation_0-rmse:0.18181 validation_1-rmse:0.14206
[57] validation_0-rmse:0.18109 validation_1-rmse:0.14106
[58] validation_0-rmse:0.18033 validation_1-rmse:0.13996
[59] validation_0-rmse:0.17964 validation_1-rmse:0.13905
[60] validation_0-rmse:0.17921 validation_1-rmse:0.13820
[61] validation_0-rmse:0.17865 validation_1-rmse:0.13731
[62] validation_0-rmse:0.17795 validation_1-rmse:0.13648
[63] validation_0-rmse:0.17737 validation_1-rmse:0.13559
[64] validation_0-rmse:0.17680 validation_1-rmse:0.13483
[65] validation_0-rmse:0.17628 validation_1-rmse:0.13408
[66] validation_0-rmse:0.17588 validation_1-rmse:0.13303
[67] validation_0-rmse:0.17530 validation_1-rmse:0.13228
[68] validation_0-rmse:0.17478 validation_1-rmse:0.13153
[69] validation_0-rmse:0.17439 validation_1-rmse:0.13081
[70] validation_0-rmse:0.17401 validation_1-rmse:0.12991
[71] validation_0-rmse:0.17347 validation_1-rmse:0.12911
[72] validation_0-rmse:0.17304 validation_1-rmse:0.12838
[73] validation_0-rmse:0.17254 validation_1-rmse:0.12774
[74] validation_0-rmse:0.17207 validation_1-rmse:0.12656
[75] validation_0-rmse:0.17185 validation_1-rmse:0.12571
[76] validation_0-rmse:0.17126 validation_1-rmse:0.12512
[77] validation_0-rmse:0.17096 validation_1-rmse:0.12447
[78] validation_0-rmse:0.17064 validation_1-rmse:0.12381
[79] validation_0-rmse:0.17024 validation_1-rmse:0.12300
[80] validation_0-rmse:0.16989 validation_1-rmse:0.12244
[81] validation_0-rmse:0.16955 validation_1-rmse:0.12180
[82] validation_0-rmse:0.16924 validation_1-rmse:0.12129
[83] validation_0-rmse:0.16931 validation_1-rmse:0.12037
[84] validation_0-rmse:0.16888 validation_1-rmse:0.11970
[85] validation_0-rmse:0.16845 validation_1-rmse:0.11914
[86] validation_0-rmse:0.16809 validation_1-rmse:0.11840
[87] validation_0-rmse:0.16766 validation_1-rmse:0.11760
[88] validation_0-rmse:0.16741 validation_1-rmse:0.11714
[89] validation_0-rmse:0.16707 validation_1-rmse:0.11667
[90] validation_0-rmse:0.16683 validation_1-rmse:0.11592
[91] validation_0-rmse:0.16643 validation_1-rmse:0.11537
[92] validation_0-rmse:0.16621 validation_1-rmse:0.11455
[93] validation_0-rmse:0.16611 validation_1-rmse:0.11396
[94] validation_0-rmse:0.16587 validation_1-rmse:0.11350
[95] validation_0-rmse:0.16563 validation_1-rmse:0.11308
[96] validation_0-rmse:0.16535 validation_1-rmse:0.11237
[97] validation_0-rmse:0.16487 validation_1-rmse:0.11173
[98] validation_0-rmse:0.16461 validation_1-rmse:0.11133
[99] validation_0-rmse:0.16437 validation_1-rmse:0.11096
2025-04-29 01:23:33,864 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training SOL/USDT (6.22 secs) --------------------
2025-04-29 01:23:33,865 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:34,396 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2024-12-22 00:00:00 to 2025-01-21 00:00:00, 3/11 trains
2025-04-29 01:23:34,397 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1737417600_prediction.feather
2025-04-29 01:23:34,401 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:34,407 - FreqaiExampleStrategy - INFO - 目标列形状:(24050,)
2025-04-29 01:23:34,409 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.97721
1 0.003044 49.97721
2 0.000465 49.97721
3 -0.000380 49.97721
4 0.002829 49.97721
2025-04-29 01:23:34,416 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:34,422 - FreqaiExampleStrategy - INFO - 目标列形状:(28850,)
2025-04-29 01:23:34,424 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.941408
1 0.003044 49.941408
2 0.000465 49.941408
3 -0.000380 49.941408
4 0.002829 49.941408
2025-04-29 01:23:34,429 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1737417600/cb_sol_1737417600
2025-04-29 01:23:34,430 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:23:34,454 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:34,454 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2024-12-22 to 2025-01-20 --------------------
2025-04-29 01:23:39,621 - datasieve.pipeline - INFO - DI tossed 1523 predictions for being too far from training data.
2025-04-29 01:23:39,624 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 111 features
2025-04-29 01:23:39,624 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.30838 validation_1-rmse:0.28356
[1] validation_0-rmse:0.30280 validation_1-rmse:0.27752
[2] validation_0-rmse:0.29759 validation_1-rmse:0.27179
[3] validation_0-rmse:0.29330 validation_1-rmse:0.26614
[4] validation_0-rmse:0.28936 validation_1-rmse:0.26091
[5] validation_0-rmse:0.28544 validation_1-rmse:0.25581
[6] validation_0-rmse:0.28151 validation_1-rmse:0.25102
[7] validation_0-rmse:0.27790 validation_1-rmse:0.24636
[8] validation_0-rmse:0.27429 validation_1-rmse:0.24196
[9] validation_0-rmse:0.27104 validation_1-rmse:0.23770
[10] validation_0-rmse:0.26762 validation_1-rmse:0.23356
[11] validation_0-rmse:0.26472 validation_1-rmse:0.22966
[12] validation_0-rmse:0.26219 validation_1-rmse:0.22601
[13] validation_0-rmse:0.25924 validation_1-rmse:0.22234
[14] validation_0-rmse:0.25634 validation_1-rmse:0.21888
[15] validation_0-rmse:0.25379 validation_1-rmse:0.21545
[16] validation_0-rmse:0.25117 validation_1-rmse:0.21221
[17] validation_0-rmse:0.24877 validation_1-rmse:0.20902
[18] validation_0-rmse:0.24653 validation_1-rmse:0.20604
[19] validation_0-rmse:0.24404 validation_1-rmse:0.20315
[20] validation_0-rmse:0.24194 validation_1-rmse:0.20032
[21] validation_0-rmse:0.23966 validation_1-rmse:0.19765
[22] validation_0-rmse:0.23804 validation_1-rmse:0.19481
[23] validation_0-rmse:0.23599 validation_1-rmse:0.19230
[24] validation_0-rmse:0.23384 validation_1-rmse:0.18993
[25] validation_0-rmse:0.23196 validation_1-rmse:0.18756
[26] validation_0-rmse:0.23057 validation_1-rmse:0.18506
[27] validation_0-rmse:0.22854 validation_1-rmse:0.18283
[28] validation_0-rmse:0.22705 validation_1-rmse:0.18071
[29] validation_0-rmse:0.22557 validation_1-rmse:0.17851
[30] validation_0-rmse:0.22394 validation_1-rmse:0.17644
[31] validation_0-rmse:0.22213 validation_1-rmse:0.17452
[32] validation_0-rmse:0.22064 validation_1-rmse:0.17267
[33] validation_0-rmse:0.21905 validation_1-rmse:0.17084
[34] validation_0-rmse:0.21806 validation_1-rmse:0.16880
[35] validation_0-rmse:0.21693 validation_1-rmse:0.16700
[36] validation_0-rmse:0.21537 validation_1-rmse:0.16520
[37] validation_0-rmse:0.21417 validation_1-rmse:0.16362
[38] validation_0-rmse:0.21282 validation_1-rmse:0.16204
[39] validation_0-rmse:0.21137 validation_1-rmse:0.16047
[40] validation_0-rmse:0.20994 validation_1-rmse:0.15897
[41] validation_0-rmse:0.20878 validation_1-rmse:0.15747
[42] validation_0-rmse:0.20766 validation_1-rmse:0.15604
[43] validation_0-rmse:0.20666 validation_1-rmse:0.15444
[44] validation_0-rmse:0.20566 validation_1-rmse:0.15316
[45] validation_0-rmse:0.20496 validation_1-rmse:0.15162
[46] validation_0-rmse:0.20394 validation_1-rmse:0.15038
[47] validation_0-rmse:0.20277 validation_1-rmse:0.14909
[48] validation_0-rmse:0.20176 validation_1-rmse:0.14793
[49] validation_0-rmse:0.20072 validation_1-rmse:0.14681
[50] validation_0-rmse:0.20058 validation_1-rmse:0.14528
[51] validation_0-rmse:0.19970 validation_1-rmse:0.14419
[52] validation_0-rmse:0.19887 validation_1-rmse:0.14284
[53] validation_0-rmse:0.19809 validation_1-rmse:0.14182
[54] validation_0-rmse:0.19725 validation_1-rmse:0.14076
[55] validation_0-rmse:0.19636 validation_1-rmse:0.13981
[56] validation_0-rmse:0.19615 validation_1-rmse:0.13853
[57] validation_0-rmse:0.19540 validation_1-rmse:0.13757
[58] validation_0-rmse:0.19460 validation_1-rmse:0.13664
[59] validation_0-rmse:0.19418 validation_1-rmse:0.13553
[60] validation_0-rmse:0.19382 validation_1-rmse:0.13445
[61] validation_0-rmse:0.19302 validation_1-rmse:0.13363
[62] validation_0-rmse:0.19218 validation_1-rmse:0.13270
[63] validation_0-rmse:0.19154 validation_1-rmse:0.13183
[64] validation_0-rmse:0.19083 validation_1-rmse:0.13105
[65] validation_0-rmse:0.19005 validation_1-rmse:0.13008
[66] validation_0-rmse:0.18929 validation_1-rmse:0.12932
[67] validation_0-rmse:0.18885 validation_1-rmse:0.12851
[68] validation_0-rmse:0.18837 validation_1-rmse:0.12781
[69] validation_0-rmse:0.18790 validation_1-rmse:0.12711
[70] validation_0-rmse:0.18732 validation_1-rmse:0.12617
[71] validation_0-rmse:0.18682 validation_1-rmse:0.12552
[72] validation_0-rmse:0.18669 validation_1-rmse:0.12448
[73] validation_0-rmse:0.18617 validation_1-rmse:0.12382
[74] validation_0-rmse:0.18587 validation_1-rmse:0.12322
[75] validation_0-rmse:0.18544 validation_1-rmse:0.12261
[76] validation_0-rmse:0.18524 validation_1-rmse:0.12162
[77] validation_0-rmse:0.18486 validation_1-rmse:0.12098
[78] validation_0-rmse:0.18443 validation_1-rmse:0.12021
[79] validation_0-rmse:0.18415 validation_1-rmse:0.11963
[80] validation_0-rmse:0.18393 validation_1-rmse:0.11866
[81] validation_0-rmse:0.18344 validation_1-rmse:0.11809
[82] validation_0-rmse:0.18307 validation_1-rmse:0.11748
[83] validation_0-rmse:0.18257 validation_1-rmse:0.11699
[84] validation_0-rmse:0.18216 validation_1-rmse:0.11643
[85] validation_0-rmse:0.18188 validation_1-rmse:0.11595
[86] validation_0-rmse:0.18168 validation_1-rmse:0.11502
[87] validation_0-rmse:0.18148 validation_1-rmse:0.11451
[88] validation_0-rmse:0.18093 validation_1-rmse:0.11378
[89] validation_0-rmse:0.18054 validation_1-rmse:0.11332
[90] validation_0-rmse:0.18024 validation_1-rmse:0.11285
[91] validation_0-rmse:0.17982 validation_1-rmse:0.11241
[92] validation_0-rmse:0.17950 validation_1-rmse:0.11185
[93] validation_0-rmse:0.17918 validation_1-rmse:0.11123
[94] validation_0-rmse:0.17882 validation_1-rmse:0.11072
[95] validation_0-rmse:0.17881 validation_1-rmse:0.10986
[96] validation_0-rmse:0.17832 validation_1-rmse:0.10941
[97] validation_0-rmse:0.17800 validation_1-rmse:0.10897
[98] validation_0-rmse:0.17774 validation_1-rmse:0.10859
[99] validation_0-rmse:0.17746 validation_1-rmse:0.10819
2025-04-29 01:23:40,890 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training SOL/USDT (6.46 secs) --------------------
2025-04-29 01:23:40,891 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:41,442 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2025-01-01 00:00:00 to 2025-01-31 00:00:00, 4/11 trains
2025-04-29 01:23:41,442 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1738281600_prediction.feather
2025-04-29 01:23:41,447 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:41,453 - FreqaiExampleStrategy - INFO - 目标列形状:(28850,)
2025-04-29 01:23:41,454 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.941408
1 0.003044 49.941408
2 0.000465 49.941408
3 -0.000380 49.941408
4 0.002829 49.941408
2025-04-29 01:23:41,460 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:41,466 - FreqaiExampleStrategy - INFO - 目标列形状:(33650,)
2025-04-29 01:23:41,468 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.830756
1 0.003044 49.830756
2 0.000465 49.830756
3 -0.000380 49.830756
4 0.002829 49.830756
2025-04-29 01:23:41,473 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1738281600/cb_sol_1738281600
2025-04-29 01:23:41,474 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:23:41,497 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:41,497 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-01 to 2025-01-30 --------------------
2025-04-29 01:23:46,635 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 111 features
2025-04-29 01:23:46,635 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.29494 validation_1-rmse:0.28739
[1] validation_0-rmse:0.28930 validation_1-rmse:0.28164
[2] validation_0-rmse:0.28437 validation_1-rmse:0.27613
[3] validation_0-rmse:0.27990 validation_1-rmse:0.27106
[4] validation_0-rmse:0.27541 validation_1-rmse:0.26617
[5] validation_0-rmse:0.27070 validation_1-rmse:0.26147
[6] validation_0-rmse:0.26683 validation_1-rmse:0.25687
[7] validation_0-rmse:0.26280 validation_1-rmse:0.25263
[8] validation_0-rmse:0.25916 validation_1-rmse:0.24830
[9] validation_0-rmse:0.25540 validation_1-rmse:0.24420
[10] validation_0-rmse:0.25186 validation_1-rmse:0.24022
[11] validation_0-rmse:0.24829 validation_1-rmse:0.23647
[12] validation_0-rmse:0.24504 validation_1-rmse:0.23286
[13] validation_0-rmse:0.24183 validation_1-rmse:0.22943
[14] validation_0-rmse:0.23870 validation_1-rmse:0.22619
[15] validation_0-rmse:0.23587 validation_1-rmse:0.22274
[16] validation_0-rmse:0.23325 validation_1-rmse:0.21951
[17] validation_0-rmse:0.23045 validation_1-rmse:0.21650
[18] validation_0-rmse:0.22792 validation_1-rmse:0.21367
[19] validation_0-rmse:0.22524 validation_1-rmse:0.21092
[20] validation_0-rmse:0.22293 validation_1-rmse:0.20804
[21] validation_0-rmse:0.22055 validation_1-rmse:0.20549
[22] validation_0-rmse:0.21831 validation_1-rmse:0.20307
[23] validation_0-rmse:0.21601 validation_1-rmse:0.20062
[24] validation_0-rmse:0.21372 validation_1-rmse:0.19810
[25] validation_0-rmse:0.21154 validation_1-rmse:0.19580
[26] validation_0-rmse:0.20966 validation_1-rmse:0.19369
[27] validation_0-rmse:0.20790 validation_1-rmse:0.19130
[28] validation_0-rmse:0.20602 validation_1-rmse:0.18921
[29] validation_0-rmse:0.20418 validation_1-rmse:0.18723
[30] validation_0-rmse:0.20236 validation_1-rmse:0.18525
[31] validation_0-rmse:0.20057 validation_1-rmse:0.18324
[32] validation_0-rmse:0.19900 validation_1-rmse:0.18144
[33] validation_0-rmse:0.19744 validation_1-rmse:0.17941
[34] validation_0-rmse:0.19608 validation_1-rmse:0.17767
[35] validation_0-rmse:0.19467 validation_1-rmse:0.17605
[36] validation_0-rmse:0.19313 validation_1-rmse:0.17422
[37] validation_0-rmse:0.19156 validation_1-rmse:0.17260
[38] validation_0-rmse:0.19020 validation_1-rmse:0.17103
[39] validation_0-rmse:0.18884 validation_1-rmse:0.16948
[40] validation_0-rmse:0.18767 validation_1-rmse:0.16797
[41] validation_0-rmse:0.18636 validation_1-rmse:0.16647
[42] validation_0-rmse:0.18512 validation_1-rmse:0.16505
[43] validation_0-rmse:0.18403 validation_1-rmse:0.16340
[44] validation_0-rmse:0.18290 validation_1-rmse:0.16210
[45] validation_0-rmse:0.18189 validation_1-rmse:0.16085
[46] validation_0-rmse:0.18090 validation_1-rmse:0.15966
[47] validation_0-rmse:0.17992 validation_1-rmse:0.15841
[48] validation_0-rmse:0.17901 validation_1-rmse:0.15728
[49] validation_0-rmse:0.17817 validation_1-rmse:0.15582
[50] validation_0-rmse:0.17697 validation_1-rmse:0.15458
[51] validation_0-rmse:0.17607 validation_1-rmse:0.15349
[52] validation_0-rmse:0.17516 validation_1-rmse:0.15235
[53] validation_0-rmse:0.17425 validation_1-rmse:0.15131
[54] validation_0-rmse:0.17347 validation_1-rmse:0.15032
[55] validation_0-rmse:0.17275 validation_1-rmse:0.14932
[56] validation_0-rmse:0.17211 validation_1-rmse:0.14834
[57] validation_0-rmse:0.17131 validation_1-rmse:0.14741
[58] validation_0-rmse:0.17072 validation_1-rmse:0.14617
[59] validation_0-rmse:0.16999 validation_1-rmse:0.14528
[60] validation_0-rmse:0.16934 validation_1-rmse:0.14416
[61] validation_0-rmse:0.16887 validation_1-rmse:0.14321
[62] validation_0-rmse:0.16842 validation_1-rmse:0.14213
[63] validation_0-rmse:0.16765 validation_1-rmse:0.14130
[64] validation_0-rmse:0.16691 validation_1-rmse:0.14048
[65] validation_0-rmse:0.16629 validation_1-rmse:0.13956
[66] validation_0-rmse:0.16565 validation_1-rmse:0.13882
[67] validation_0-rmse:0.16530 validation_1-rmse:0.13793
[68] validation_0-rmse:0.16467 validation_1-rmse:0.13710
[69] validation_0-rmse:0.16436 validation_1-rmse:0.13621
[70] validation_0-rmse:0.16377 validation_1-rmse:0.13542
[71] validation_0-rmse:0.16334 validation_1-rmse:0.13463
[72] validation_0-rmse:0.16280 validation_1-rmse:0.13394
[73] validation_0-rmse:0.16230 validation_1-rmse:0.13328
[74] validation_0-rmse:0.16156 validation_1-rmse:0.13246
[75] validation_0-rmse:0.16122 validation_1-rmse:0.13151
[76] validation_0-rmse:0.16080 validation_1-rmse:0.13080
[77] validation_0-rmse:0.16033 validation_1-rmse:0.13015
[78] validation_0-rmse:0.15992 validation_1-rmse:0.12951
[79] validation_0-rmse:0.15950 validation_1-rmse:0.12888
[80] validation_0-rmse:0.15909 validation_1-rmse:0.12822
[81] validation_0-rmse:0.15875 validation_1-rmse:0.12744
[82] validation_0-rmse:0.15831 validation_1-rmse:0.12683
[83] validation_0-rmse:0.15786 validation_1-rmse:0.12626
[84] validation_0-rmse:0.15747 validation_1-rmse:0.12572
[85] validation_0-rmse:0.15724 validation_1-rmse:0.12495
[86] validation_0-rmse:0.15695 validation_1-rmse:0.12442
[87] validation_0-rmse:0.15664 validation_1-rmse:0.12382
[88] validation_0-rmse:0.15651 validation_1-rmse:0.12326
[89] validation_0-rmse:0.15629 validation_1-rmse:0.12256
[90] validation_0-rmse:0.15596 validation_1-rmse:0.12196
[91] validation_0-rmse:0.15559 validation_1-rmse:0.12141
[92] validation_0-rmse:0.15511 validation_1-rmse:0.12088
[93] validation_0-rmse:0.15487 validation_1-rmse:0.12033
[94] validation_0-rmse:0.15472 validation_1-rmse:0.11975
[95] validation_0-rmse:0.15438 validation_1-rmse:0.11924
[96] validation_0-rmse:0.15408 validation_1-rmse:0.11882
[97] validation_0-rmse:0.15382 validation_1-rmse:0.11819
[98] validation_0-rmse:0.15350 validation_1-rmse:0.11777
[99] validation_0-rmse:0.15331 validation_1-rmse:0.11727
2025-04-29 01:23:47,608 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training SOL/USDT (6.13 secs) --------------------
2025-04-29 01:23:47,608 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:48,148 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2025-01-11 00:00:00 to 2025-02-10 00:00:00, 5/11 trains
2025-04-29 01:23:48,148 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1739145600_prediction.feather
2025-04-29 01:23:48,156 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:48,162 - FreqaiExampleStrategy - INFO - 目标列形状:(33650,)
2025-04-29 01:23:48,163 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.830756
1 0.003044 49.830756
2 0.000465 49.830756
3 -0.000380 49.830756
4 0.002829 49.830756
2025-04-29 01:23:48,169 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:48,175 - FreqaiExampleStrategy - INFO - 目标列形状:(38450,)
2025-04-29 01:23:48,177 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.714422
1 0.003044 49.714422
2 0.000465 49.714422
3 -0.000380 49.714422
4 0.002829 49.714422
2025-04-29 01:23:48,182 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1739145600/cb_sol_1739145600
2025-04-29 01:23:48,183 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:23:48,205 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:48,206 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-11 to 2025-02-09 --------------------
2025-04-29 01:23:53,217 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 111 features
2025-04-29 01:23:53,218 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.29889 validation_1-rmse:0.30153
[1] validation_0-rmse:0.29317 validation_1-rmse:0.29483
[2] validation_0-rmse:0.28819 validation_1-rmse:0.28860
[3] validation_0-rmse:0.28336 validation_1-rmse:0.28273
[4] validation_0-rmse:0.27885 validation_1-rmse:0.27694
[5] validation_0-rmse:0.27448 validation_1-rmse:0.27155
[6] validation_0-rmse:0.27020 validation_1-rmse:0.26634
[7] validation_0-rmse:0.26629 validation_1-rmse:0.26134
[8] validation_0-rmse:0.26241 validation_1-rmse:0.25653
[9] validation_0-rmse:0.25876 validation_1-rmse:0.25192
[10] validation_0-rmse:0.25559 validation_1-rmse:0.24747
[11] validation_0-rmse:0.25223 validation_1-rmse:0.24337
[12] validation_0-rmse:0.24904 validation_1-rmse:0.23934
[13] validation_0-rmse:0.24639 validation_1-rmse:0.23548
[14] validation_0-rmse:0.24353 validation_1-rmse:0.23187
[15] validation_0-rmse:0.24076 validation_1-rmse:0.22837
[16] validation_0-rmse:0.23849 validation_1-rmse:0.22484
[17] validation_0-rmse:0.23581 validation_1-rmse:0.22147
[18] validation_0-rmse:0.23342 validation_1-rmse:0.21814
[19] validation_0-rmse:0.23133 validation_1-rmse:0.21509
[20] validation_0-rmse:0.22937 validation_1-rmse:0.21187
[21] validation_0-rmse:0.22713 validation_1-rmse:0.20902
[22] validation_0-rmse:0.22509 validation_1-rmse:0.20631
[23] validation_0-rmse:0.22312 validation_1-rmse:0.20373
[24] validation_0-rmse:0.22123 validation_1-rmse:0.20076
[25] validation_0-rmse:0.21951 validation_1-rmse:0.19837
[26] validation_0-rmse:0.21751 validation_1-rmse:0.19562
[27] validation_0-rmse:0.21589 validation_1-rmse:0.19309
[28] validation_0-rmse:0.21422 validation_1-rmse:0.19091
[29] validation_0-rmse:0.21272 validation_1-rmse:0.18879
[30] validation_0-rmse:0.21119 validation_1-rmse:0.18660
[31] validation_0-rmse:0.20982 validation_1-rmse:0.18468
[32] validation_0-rmse:0.20829 validation_1-rmse:0.18239
[33] validation_0-rmse:0.20681 validation_1-rmse:0.18048
[34] validation_0-rmse:0.20548 validation_1-rmse:0.17869
[35] validation_0-rmse:0.20431 validation_1-rmse:0.17665
[36] validation_0-rmse:0.20297 validation_1-rmse:0.17483
[37] validation_0-rmse:0.20174 validation_1-rmse:0.17311
[38] validation_0-rmse:0.20060 validation_1-rmse:0.17153
[39] validation_0-rmse:0.19951 validation_1-rmse:0.16958
[40] validation_0-rmse:0.19848 validation_1-rmse:0.16805
[41] validation_0-rmse:0.19745 validation_1-rmse:0.16652
[42] validation_0-rmse:0.19647 validation_1-rmse:0.16509
[43] validation_0-rmse:0.19570 validation_1-rmse:0.16325
[44] validation_0-rmse:0.19473 validation_1-rmse:0.16187
[45] validation_0-rmse:0.19397 validation_1-rmse:0.16012
[46] validation_0-rmse:0.19314 validation_1-rmse:0.15887
[47] validation_0-rmse:0.19196 validation_1-rmse:0.15723
[48] validation_0-rmse:0.19096 validation_1-rmse:0.15595
[49] validation_0-rmse:0.19009 validation_1-rmse:0.15468
[50] validation_0-rmse:0.18931 validation_1-rmse:0.15355
[51] validation_0-rmse:0.18864 validation_1-rmse:0.15207
[52] validation_0-rmse:0.18786 validation_1-rmse:0.15101
[53] validation_0-rmse:0.18690 validation_1-rmse:0.14960
[54] validation_0-rmse:0.18614 validation_1-rmse:0.14859
[55] validation_0-rmse:0.18550 validation_1-rmse:0.14756
[56] validation_0-rmse:0.18475 validation_1-rmse:0.14647
[57] validation_0-rmse:0.18405 validation_1-rmse:0.14545
[58] validation_0-rmse:0.18346 validation_1-rmse:0.14415
[59] validation_0-rmse:0.18277 validation_1-rmse:0.14321
[60] validation_0-rmse:0.18219 validation_1-rmse:0.14221
[61] validation_0-rmse:0.18158 validation_1-rmse:0.14129
[62] validation_0-rmse:0.18100 validation_1-rmse:0.14043
[63] validation_0-rmse:0.18059 validation_1-rmse:0.13920
[64] validation_0-rmse:0.17997 validation_1-rmse:0.13842
[65] validation_0-rmse:0.17941 validation_1-rmse:0.13754
[66] validation_0-rmse:0.17881 validation_1-rmse:0.13652
[67] validation_0-rmse:0.17823 validation_1-rmse:0.13576
[68] validation_0-rmse:0.17784 validation_1-rmse:0.13468
[69] validation_0-rmse:0.17735 validation_1-rmse:0.13396
[70] validation_0-rmse:0.17687 validation_1-rmse:0.13311
[71] validation_0-rmse:0.17628 validation_1-rmse:0.13225
[72] validation_0-rmse:0.17599 validation_1-rmse:0.13154
[73] validation_0-rmse:0.17542 validation_1-rmse:0.13080
[74] validation_0-rmse:0.17497 validation_1-rmse:0.13013
[75] validation_0-rmse:0.17456 validation_1-rmse:0.12954
[76] validation_0-rmse:0.17416 validation_1-rmse:0.12864
[77] validation_0-rmse:0.17369 validation_1-rmse:0.12802
[78] validation_0-rmse:0.17345 validation_1-rmse:0.12735
[79] validation_0-rmse:0.17302 validation_1-rmse:0.12672
[80] validation_0-rmse:0.17254 validation_1-rmse:0.12609
[81] validation_0-rmse:0.17248 validation_1-rmse:0.12527
[82] validation_0-rmse:0.17210 validation_1-rmse:0.12470
[83] validation_0-rmse:0.17196 validation_1-rmse:0.12398
[84] validation_0-rmse:0.17189 validation_1-rmse:0.12334
[85] validation_0-rmse:0.17155 validation_1-rmse:0.12280
[86] validation_0-rmse:0.17124 validation_1-rmse:0.12230
[87] validation_0-rmse:0.17103 validation_1-rmse:0.12178
[88] validation_0-rmse:0.17086 validation_1-rmse:0.12118
[89] validation_0-rmse:0.17064 validation_1-rmse:0.12049
[90] validation_0-rmse:0.17029 validation_1-rmse:0.11993
[91] validation_0-rmse:0.16981 validation_1-rmse:0.11942
[92] validation_0-rmse:0.16950 validation_1-rmse:0.11894
[93] validation_0-rmse:0.16937 validation_1-rmse:0.11833
[94] validation_0-rmse:0.16928 validation_1-rmse:0.11786
[95] validation_0-rmse:0.16899 validation_1-rmse:0.11735
[96] validation_0-rmse:0.16869 validation_1-rmse:0.11693
[97] validation_0-rmse:0.16843 validation_1-rmse:0.11650
[98] validation_0-rmse:0.16829 validation_1-rmse:0.11591
[99] validation_0-rmse:0.16802 validation_1-rmse:0.11547
2025-04-29 01:23:54,194 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training SOL/USDT (6.01 secs) --------------------
2025-04-29 01:23:54,194 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:23:54,764 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2025-01-21 00:00:00 to 2025-02-20 00:00:00, 6/11 trains
2025-04-29 01:23:54,765 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1740009600_prediction.feather
2025-04-29 01:23:54,773 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:54,779 - FreqaiExampleStrategy - INFO - 目标列形状:(38450,)
2025-04-29 01:23:54,780 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.714422
1 0.003044 49.714422
2 0.000465 49.714422
3 -0.000380 49.714422
4 0.002829 49.714422
2025-04-29 01:23:54,790 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:23:54,797 - FreqaiExampleStrategy - INFO - 目标列形状:(43250,)
2025-04-29 01:23:54,798 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.626186
1 0.003044 49.626186
2 0.000465 49.626186
3 -0.000380 49.626186
4 0.002829 49.626186
2025-04-29 01:23:54,804 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1740009600/cb_sol_1740009600
2025-04-29 01:23:54,804 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:23:54,827 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:23:54,828 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-21 to 2025-02-19 --------------------
2025-04-29 01:23:59,967 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 111 features
2025-04-29 01:23:59,968 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - Training model on 11520 data points
[0] validation_0-rmse:0.29357 validation_1-rmse:0.28852
[1] validation_0-rmse:0.28850 validation_1-rmse:0.28219
[2] validation_0-rmse:0.28292 validation_1-rmse:0.27618
[3] validation_0-rmse:0.27862 validation_1-rmse:0.27046
[4] validation_0-rmse:0.27383 validation_1-rmse:0.26510
[5] validation_0-rmse:0.27018 validation_1-rmse:0.25989
[6] validation_0-rmse:0.26615 validation_1-rmse:0.25477
[7] validation_0-rmse:0.26234 validation_1-rmse:0.25007
[8] validation_0-rmse:0.25794 validation_1-rmse:0.24560
[9] validation_0-rmse:0.25417 validation_1-rmse:0.24109
[10] validation_0-rmse:0.25083 validation_1-rmse:0.23700
[11] validation_0-rmse:0.24683 validation_1-rmse:0.23303
[12] validation_0-rmse:0.24384 validation_1-rmse:0.22908
[13] validation_0-rmse:0.24093 validation_1-rmse:0.22542
[14] validation_0-rmse:0.23743 validation_1-rmse:0.22186
[15] validation_0-rmse:0.23484 validation_1-rmse:0.21841
[16] validation_0-rmse:0.23215 validation_1-rmse:0.21525
[17] validation_0-rmse:0.22951 validation_1-rmse:0.21206
[18] validation_0-rmse:0.22658 validation_1-rmse:0.20906
[19] validation_0-rmse:0.22440 validation_1-rmse:0.20615
[20] validation_0-rmse:0.22193 validation_1-rmse:0.20314
[21] validation_0-rmse:0.22009 validation_1-rmse:0.20016
[22] validation_0-rmse:0.21755 validation_1-rmse:0.19751
[23] validation_0-rmse:0.21578 validation_1-rmse:0.19498
[24] validation_0-rmse:0.21440 validation_1-rmse:0.19241
[25] validation_0-rmse:0.21229 validation_1-rmse:0.19006
[26] validation_0-rmse:0.21038 validation_1-rmse:0.18780
[27] validation_0-rmse:0.20897 validation_1-rmse:0.18529
[28] validation_0-rmse:0.20703 validation_1-rmse:0.18313
[29] validation_0-rmse:0.20556 validation_1-rmse:0.18091
[30] validation_0-rmse:0.20384 validation_1-rmse:0.17884
[31] validation_0-rmse:0.20281 validation_1-rmse:0.17690
[32] validation_0-rmse:0.20169 validation_1-rmse:0.17483
[33] validation_0-rmse:0.20012 validation_1-rmse:0.17300
[34] validation_0-rmse:0.19876 validation_1-rmse:0.17106
[35] validation_0-rmse:0.19755 validation_1-rmse:0.16934
[36] validation_0-rmse:0.19649 validation_1-rmse:0.16752
[37] validation_0-rmse:0.19501 validation_1-rmse:0.16586
[38] validation_0-rmse:0.19423 validation_1-rmse:0.16418
[39] validation_0-rmse:0.19297 validation_1-rmse:0.16264
[40] validation_0-rmse:0.19162 validation_1-rmse:0.16092
[41] validation_0-rmse:0.19049 validation_1-rmse:0.15952
[42] validation_0-rmse:0.18925 validation_1-rmse:0.15810
[43] validation_0-rmse:0.18845 validation_1-rmse:0.15638
[44] validation_0-rmse:0.18730 validation_1-rmse:0.15506
[45] validation_0-rmse:0.18661 validation_1-rmse:0.15357
[46] validation_0-rmse:0.18563 validation_1-rmse:0.15226
[47] validation_0-rmse:0.18473 validation_1-rmse:0.15101
[48] validation_0-rmse:0.18399 validation_1-rmse:0.14957
[49] validation_0-rmse:0.18304 validation_1-rmse:0.14841
[50] validation_0-rmse:0.18219 validation_1-rmse:0.14717
[51] validation_0-rmse:0.18131 validation_1-rmse:0.14599
[52] validation_0-rmse:0.18043 validation_1-rmse:0.14492
[53] validation_0-rmse:0.17966 validation_1-rmse:0.14388
[54] validation_0-rmse:0.17901 validation_1-rmse:0.14274
[55] validation_0-rmse:0.17850 validation_1-rmse:0.14134
[56] validation_0-rmse:0.17764 validation_1-rmse:0.14035
[57] validation_0-rmse:0.17682 validation_1-rmse:0.13937
[58] validation_0-rmse:0.17604 validation_1-rmse:0.13844
[59] validation_0-rmse:0.17526 validation_1-rmse:0.13754
[60] validation_0-rmse:0.17488 validation_1-rmse:0.13621
[61] validation_0-rmse:0.17432 validation_1-rmse:0.13530
[62] validation_0-rmse:0.17345 validation_1-rmse:0.13439
[63] validation_0-rmse:0.17284 validation_1-rmse:0.13358
[64] validation_0-rmse:0.17213 validation_1-rmse:0.13278
[65] validation_0-rmse:0.17164 validation_1-rmse:0.13175
[66] validation_0-rmse:0.17098 validation_1-rmse:0.13088
[67] validation_0-rmse:0.17049 validation_1-rmse:0.13002
[68] validation_0-rmse:0.17000 validation_1-rmse:0.12918
[69] validation_0-rmse:0.16969 validation_1-rmse:0.12815
[70] validation_0-rmse:0.16917 validation_1-rmse:0.12746
[71] validation_0-rmse:0.16857 validation_1-rmse:0.12678
[72] validation_0-rmse:0.16830 validation_1-rmse:0.12595
[73] validation_0-rmse:0.16793 validation_1-rmse:0.12522
[74] validation_0-rmse:0.16752 validation_1-rmse:0.12457
[75] validation_0-rmse:0.16704 validation_1-rmse:0.12395
[76] validation_0-rmse:0.16668 validation_1-rmse:0.12316
[77] validation_0-rmse:0.16621 validation_1-rmse:0.12251
[78] validation_0-rmse:0.16591 validation_1-rmse:0.12185
[79] validation_0-rmse:0.16550 validation_1-rmse:0.12115
[80] validation_0-rmse:0.16506 validation_1-rmse:0.12055
[81] validation_0-rmse:0.16467 validation_1-rmse:0.12001
[82] validation_0-rmse:0.16422 validation_1-rmse:0.11944
[83] validation_0-rmse:0.16379 validation_1-rmse:0.11892
[84] validation_0-rmse:0.16344 validation_1-rmse:0.11825
[85] validation_0-rmse:0.16317 validation_1-rmse:0.11766
[86] validation_0-rmse:0.16289 validation_1-rmse:0.11712
[87] validation_0-rmse:0.16271 validation_1-rmse:0.11639
[88] validation_0-rmse:0.16236 validation_1-rmse:0.11591
[89] validation_0-rmse:0.16210 validation_1-rmse:0.11515
[90] validation_0-rmse:0.16170 validation_1-rmse:0.11457
[91] validation_0-rmse:0.16149 validation_1-rmse:0.11411
[92] validation_0-rmse:0.16132 validation_1-rmse:0.11360
[93] validation_0-rmse:0.16108 validation_1-rmse:0.11292
[94] validation_0-rmse:0.16077 validation_1-rmse:0.11247
[95] validation_0-rmse:0.16040 validation_1-rmse:0.11205
[96] validation_0-rmse:0.16017 validation_1-rmse:0.11157
[97] validation_0-rmse:0.15988 validation_1-rmse:0.11117
[98] validation_0-rmse:0.15964 validation_1-rmse:0.11074
[99] validation_0-rmse:0.15958 validation_1-rmse:0.11029
2025-04-29 01:24:01,761 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Done training SOL/USDT (6.96 secs) --------------------
2025-04-29 01:24:01,762 - freqtrade.freqai.freqai_interface - INFO - Saving metadata to disk.
2025-04-29 01:24:02,314 - freqtrade.freqai.freqai_interface - INFO - Training SOL/USDT, 2/2 pairs from 2025-01-31 00:00:00 to 2025-03-02 00:00:00, 7/11 trains
2025-04-29 01:24:02,315 - freqtrade.freqai.data_kitchen - INFO - Could not find backtesting prediction file at
/freqtrade/user_data/models/test175/backtesting_predictions/cb_sol_1740873600_prediction.feather
2025-04-29 01:24:02,321 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:24:02,328 - FreqaiExampleStrategy - INFO - 目标列形状:(43250,)
2025-04-29 01:24:02,329 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.626186
1 0.003044 49.626186
2 0.000465 49.626186
3 -0.000380 49.626186
4 0.002829 49.626186
2025-04-29 01:24:02,337 - FreqaiExampleStrategy - INFO - 设置 FreqAI 目标交易对SOL/USDT
2025-04-29 01:24:02,344 - FreqaiExampleStrategy - INFO - 目标列形状:(48050,)
2025-04-29 01:24:02,345 - FreqaiExampleStrategy - INFO - 目标列预览:
up_or_down &-buy_rsi
0 0.002704 49.568812
1 0.003044 49.568812
2 0.000465 49.568812
3 -0.000380 49.568812
4 0.002829 49.568812
2025-04-29 01:24:02,351 - freqtrade.freqai.freqai_interface - INFO - Could not find model at /freqtrade/user_data/models/test175/sub-train-SOL_1740873600/cb_sol_1740873600
2025-04-29 01:24:02,352 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Starting training SOL/USDT --------------------
2025-04-29 01:24:02,376 - freqtrade.freqai.data_kitchen - INFO - SOL/USDT: dropped 0 training points due to NaNs in populated dataset 14400.
2025-04-29 01:24:02,376 - freqtrade.freqai.base_models.BaseRegressionModel - INFO - -------------------- Training on data from 2025-01-31 to 2025-03-01 --------------------
 
 
^Z^C2025-04-29 01:24:05,324 - freqtrade - INFO - SIGINT received, aborting ...