### Model constructor and policy parameters
-| Path | Runtime fallback / requirement | Type / constraints | Supplied profile | Behavior |
-| -------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- | -------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| freqai.model_training_parameters | {} native | Dictionary | device:auto, verbose:1 | Deep-copied then normalized; remaining kwargs forwarded to chosen SB3 constructor. This is SDK boundary, not an app-owned exhaustive hyperparameter schema. |
-| freqai.model_training_parameters.seed | 42 | Integer intended; SDK validation | Omitted | Local seed default; envs derive seeds and HPO increments by trial number. |
-| freqai.model_training_parameters.gamma | 0.95 | Finite Python/NumPy integer or floating scalar in [0,1]; null, bool, string, complex and arrays rejected | Omitted | Effective value is validated after HPO/resumed-learner precedence and propagated to environment potential_gamma. Invalid persisted gamma blocks continuation. |
-| freqai.model_training_parameters.learning_rate | SDK default unless lr_schedule=true; then initial 0.0003 if omitted | SDK numeric/schedule; app wraps numeric only | Omitted | Do not call 0.0003 an unconditional app default. |
-| freqai.model_training_parameters.clip_range | SDK default unless PPO-family cr_schedule=true; then initial 0.2 if omitted | SDK numeric/schedule; app wraps numeric only | Omitted | Only PPO family schedule conversion. |
-| freqai.model_training_parameters.gpu_memory_fraction | null/omitted disables | Numeric in (0,1] intended; ignored invalid bounds/no CUDA, not robust type validation | Omitted | App-only; applies torch CUDA per-process limit to device 0, removed before SDK constructor. |
-| freqai.model_training_parameters.device | No app fallback; SDK auto | PyTorch/SB3 device specification | auto | Forwarded; doc examples auto/cpu/cuda/cuda:0 are not an app-enforced exhaustive choice list. |
-| freqai.model_training_parameters.verbose | SDK constructor default; callback lookup fallback 0 | SDK verbosity integer | 1 | Forwarded to constructor, also read for callback verbosity. |
-| freqai.model_training_parameters.policy_kwargs.net_arch | [128,128] per branch for PPO family; [128,128] for others | small\|medium\|large\|extra_large, list of layer widths; PPO family additionally {pi:[...],vf:[...]} | Omitted | Presets use two layers of 128/256/512/1024; PPO list expanded to both heads, invalid/missing head resets to [128,128]. Other families accept list or presets. Layer element validation remains SDK. |
-| freqai.model_training_parameters.policy_kwargs.activation_fn | relu | relu\|tanh\|elu\|leaky_relu | Omitted | Converted to torch class; unknown name silently falls back to ReLU. |
-| freqai.model_training_parameters.policy_kwargs.optimizer_class | adamw | adamw\|rmsprop\|adam | Omitted | Converted to torch class; unknown name falls back to Adam (not AdamW). |
-| freqai.model_training_parameters.subsample_steps | Absent | Positive integer intended; no local rejection | Omitted | DQN/QRDQN-only app convenience, removed before constructor; computes gradient_steps=min(train_freq,max(1,ceil(train_freq/subsample_steps))) when both positive integers. Otherwise -1. |
-| freqai.model_training_parameters.gradient_steps | DQN-family absent/None -> derived value, usually -1 without valid train_freq+subsample_steps | SDK integer | Omitted | Explicit non-None value retained; not an unconditional SDK-default forwarding. |
-| leverage | proposed_leverage, not fixed 1 | Finite float-convertible requested value; effective clamped [1,max_leverage] | Omitted (the commented example is not an override) | Top-level strategy field, not an RL/model parameter. Invalid/nonfinite values use the proposal; live state PnL is divided by trade leverage to align the training proxy. |
-| custom_protections | [] | List of dictionaries, each with a string method; otherwise ValueError | [] | Top-level strategy field. Protection-specific settings are delegated to Freqtrade protection plugins. An empty list does not configure custom protections. |
+| Path | Runtime fallback / requirement | Type / constraints | Supplied profile | Behavior |
+| -------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- | -------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| freqai.model_training_parameters | {} native | Dictionary | device:auto, verbose:1 | Deep-copied then normalized; remaining kwargs forwarded to chosen SB3 constructor. This is SDK boundary, not an app-owned exhaustive hyperparameter schema. |
+| freqai.model_training_parameters.seed | 42 | Integer intended; SDK validation | Omitted | Local seed default; envs derive seeds and HPO increments by trial number. |
+| freqai.model_training_parameters.gamma | 0.95 | Finite Python/NumPy integer or floating scalar in [0,1]; null, bool, string, complex and arrays rejected | Omitted | Effective value is validated after HPO/resumed-learner precedence and propagated to environment potential_gamma. Invalid persisted gamma blocks continuation. |
+| freqai.model_training_parameters.learning_rate | SDK default unless lr_schedule=true; then initial 0.0003 if omitted | SDK numeric/schedule; app wraps numeric only | Omitted | Do not call 0.0003 an unconditional app default. |
+| freqai.model_training_parameters.clip_range | SDK default unless PPO-family cr_schedule=true; then initial 0.2 if omitted | SDK numeric/schedule; app wraps numeric only | Omitted | Only PPO family schedule conversion. |
+| freqai.model_training_parameters.gpu_memory_fraction | null/omitted disables | Numeric in (0,1] intended; ignored invalid bounds/no CUDA, not robust type validation | Omitted | App-only; applies torch CUDA per-process limit to device 0, removed before SDK constructor. |
+| freqai.model_training_parameters.device | No app fallback; SDK auto | PyTorch/SB3 device specification | auto | Forwarded; doc examples auto/cpu/cuda/cuda:0 are not an app-enforced exhaustive choice list. |
+| freqai.model_training_parameters.verbose | SDK constructor default; callback lookup fallback 0 | SDK verbosity integer | 1 | Forwarded to constructor, also read for callback verbosity. |
+| freqai.model_training_parameters.policy_kwargs.net_arch | [128,128] per branch for PPO family; [128,128] for others | small\|medium\|large\|extra_large, list of layer widths; PPO family additionally {pi:[...],vf:[...]} | Omitted | Presets use two layers of 128/256/512/1024; PPO list expanded to both heads, invalid/missing head resets to [128,128]. Other families accept list or presets. Layer element validation remains SDK. |
+| freqai.model_training_parameters.policy_kwargs.activation_fn | relu | relu\|tanh\|elu\|leaky_relu | Omitted | Converted to torch class; unknown name silently falls back to ReLU. |
+| freqai.model_training_parameters.policy_kwargs.optimizer_class | adamw | adamw\|rmsprop\|adam | Omitted | Converted to torch class; unknown name falls back to Adam (not AdamW). |
+| freqai.model_training_parameters.subsample_steps | Absent | Positive integer intended; no local rejection | Omitted | DQN/QRDQN-only app convenience, removed before constructor; computes gradient_steps=min(train_freq,max(1,ceil(train_freq/subsample_steps))) when both positive integers. Otherwise -1. |
+| freqai.model_training_parameters.gradient_steps | DQN-family absent/None -> derived value, usually -1 without valid train_freq+subsample_steps | SDK integer | Omitted | Explicit non-None value retained; not an unconditional SDK-default forwarding. |
+| leverage | proposed_leverage, not fixed 1 | Finite float-convertible requested value; effective clamped [1,max_leverage] | Omitted (the commented example is not an override) | Top-level strategy field, not an RL/model parameter. Invalid/nonfinite values use the proposal; live state PnL is divided by trade leverage to align the training proxy. |
+| custom_protections | [] | List of dictionaries, each with a string method; otherwise ValueError | [] | Top-level strategy field. Protection-specific settings are delegated to Freqtrade protection plugins. An empty list does not configure custom protections. |
Unlisted algorithm-specific constructor kwargs are forwarded to the selected
SDK after application normalization; use the compatible algorithm's documented
#### Duration Penalties
-| Parameter | Default | Description |
-| ---------------------------- | ------- | ----------------------------------------------------------------------------------------- |
-| `max_trade_duration_candles` | 128 | Trade duration cap |
+| Parameter | Default | Description |
+| ---------------------------- | ------- | ------------------------------------------------------------------------------------------- |
+| `max_trade_duration_candles` | 128 | Trade duration cap |
| `max_idle_duration_candles` | None | Idle hazard threshold; missing/None derives 4× trade cap; idle clock keeps counting past it |
-| `idle_penalty_ratio` | 1.0 | Idle penalty ratio |
-| `idle_penalty_power` | 1.025 | Idle penalty exponent |
-| `hold_penalty_ratio` | 1.0 | Hold penalty ratio |
-| `hold_penalty_power` | 1.025 | Hold penalty exponent |
+| `idle_penalty_ratio` | 1.0 | Idle penalty ratio |
+| `idle_penalty_power` | 1.025 | Idle penalty exponent |
+| `hold_penalty_ratio` | 1.0 | Hold penalty ratio |
+| `hold_penalty_power` | 1.025 | Hold penalty exponent |
An explicit zero threshold uses denominator 1 and does not disable the idle
penalty.
repositories / freqai-strategies.git / commitdiff
