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 ...