Promote SAC version v2026-02-13_53ad3139 to current

README.md

@@ -8,16 +8,16 @@ tags:
 - learnfinance
 ---
 
-# LearnFinance SAC Model - v2026-01-23_4049af7e
+# LearnFinance SAC Model - v2026-02-13_53ad3139
 
 Soft Actor-Critic (SAC) portfolio allocation agent using dual forecasts (LSTM + PatchTST) as features.
 
 ## Model Details
 
-- **Version**: v2026-01-23_4049af7e
+- **Version**: v2026-02-13_53ad3139
 - **Model Type**: SAC (Soft Actor-Critic) with dual forecasts
-- **Training Window**: 2011-01-01 to 2026-01-23
-- **Symbols**: 15 stocks
+- **Training Window**: 2011-01-01 to 2026-02-13
+- **Symbols**: 14 stocks
 
 ## Components
 
@@ -30,13 +30,13 @@ Soft Actor-Critic (SAC) portfolio allocation agent using dual forecasts (LSTM +
 
 ## Metrics
 
-- Actor Loss: 0.3213101402535821
+- Actor Loss: 0.47051061680353934
 - Critic Loss: 0.0
-- Avg Episode Return: 0.2853802386733016
-- Avg Episode Sharpe: 0.22613404050736566
-- Eval Sharpe: 0.8972165609782691
-- Eval CAGR: 0.19267435023534785
-- Eval Max Drawdown: 0.13759327587214085
+- Avg Episode Return: 0.3164223983680193
+- Avg Episode Sharpe: 0.23520403538043264
+- Eval Sharpe: 1.239769458631745
+- Eval CAGR: 0.302979570589738
+- Eval Max Drawdown: 0.22627892173813877
 
 ## Usage
 
@@ -44,5 +44,5 @@ Soft Actor-Critic (SAC) portfolio allocation agent using dual forecasts (LSTM +
 from brain_api.storage.sac import SACHuggingFaceModelStorage
 
 storage = SACHuggingFaceModelStorage(repo_id="hajirazin/learnfinance-models-sac")
-artifacts = storage.download_model(version="v2026-01-23_4049af7e")
+artifacts = storage.download_model(version="v2026-02-13_53ad3139")
 ```

actor.pt

@@ -1,3 +1,3 @@
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config.json

@@ -8,7 +8,7 @@
   "critic_lr": 0.0003,
   "alpha_lr": 0.0003,
   "tau": 0.005,
-  "gamma": 0.99,
+  "gamma": 0.97,
   "auto_entropy_tuning": true,
   "target_entropy": -16.0,
   "init_alpha": 0.2,
@@ -24,11 +24,13 @@
   "cost_bps": 10,
   "cash_buffer": 0.02,
   "max_position_weight": 0.2,
-  "reward_scale": 100.0,
+  "reward_scale": 1.0,
   "n_stocks": 15,
   "seed": 42,
   "validation_years": 2,
   "min_cagr_improvement": 0.0,
+  "sharpe_weight": 0.5,
+  "sharpe_eta": 0.01,
   "training_years": 10,
   "n_eval_folds": 3
 }

critic.pt

@@ -1,3 +1,3 @@
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+size 118381

critic_target.pt

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log_alpha.pt

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 size 1591

metadata.json

@@ -1,71 +1,72 @@
 {
-    "model_type": "sac",
-    "version": "v2026-01-30_a8b6fd41",
-    "training_timestamp": "2026-02-01T10:00:17.513580+00:00",
-    "data_window": {
-        "start": "2011-01-01",
-        "end": "2026-01-30"
-    },
-    "symbols": [
-        "AAPL",
-        "NVDA",
-        "MSFT",
-        "TSM",
-        "GOOGL",
-        "META",
-        "AVGO",
-        "TSLA",
-        "SAP",
-        "LLY",
-        "XOM",
-        "JNJ",
-        "TOELY",
-        "AMD",
-        "ABBV"
+  "model_type": "sac",
+  "version": "v2026-02-13_53ad3139",
+  "training_timestamp": "2026-02-15T00:21:21.587947+00:00",
+  "data_window": {
+    "start": "2011-01-01",
+    "end": "2026-02-13"
+  },
+  "symbols": [
+    "NVDA",
+    "AAPL",
+    "MSFT",
+    "TSM",
+    "GOOGL",
+    "META",
+    "AVGO",
+    "TSLA",
+    "SAP",
+    "LLY",
+    "XOM",
+    "JNJ",
+    "TOELY",
+    "MU"
+  ],
+  "config": {
+    "hidden_sizes": [
+      64,
+      64
     ],
-    "config": {
-        "hidden_sizes": [
-            64,
-            64
-        ],
-        "activation": "relu",
-        "actor_lr": 0.0003,
-        "critic_lr": 0.0003,
-        "alpha_lr": 0.0003,
-        "tau": 0.005,
-        "gamma": 0.99,
-        "auto_entropy_tuning": true,
-        "target_entropy": -16.0,
-        "init_alpha": 0.2,
-        "buffer_size": 10000,
-        "batch_size": 64,
-        "gradient_steps_per_env_step": 1,
-        "warmup_steps": 100,
-        "total_timesteps": 10000,
-        "weight_decay": 0.0001,
-        "max_grad_norm": 1.0,
-        "q_value_clip": 100.0,
-        "normalize_rewards": true,
-        "cost_bps": 10,
-        "cash_buffer": 0.02,
-        "max_position_weight": 0.2,
-        "reward_scale": 100.0,
-        "n_stocks": 15,
-        "seed": 42,
-        "validation_years": 2,
-        "min_cagr_improvement": 0.0,
-        "training_years": 10,
-        "n_eval_folds": 3
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-    "promoted": true,
-    "prior_version": "v2026-01-23_4049af7e",
-    "metrics": {
-        "actor_loss": 0.2886562280863597,
-        "critic_loss": 0.0,
-        "avg_episode_return": 0.2663766610905494,
-        "avg_episode_sharpe": 0.21521832368342012,
-        "eval_sharpe": 0.6094980295249373,
-        "eval_cagr": 0.12633316299206254,
-        "eval_max_drawdown": 0.22111396255213112
-    }
+    "activation": "relu",
+    "actor_lr": 0.0003,
+    "critic_lr": 0.0003,
+    "alpha_lr": 0.0003,
+    "tau": 0.005,
+    "gamma": 0.97,
+    "auto_entropy_tuning": true,
+    "target_entropy": -16.0,
+    "init_alpha": 0.2,
+    "buffer_size": 10000,
+    "batch_size": 64,
+    "gradient_steps_per_env_step": 1,
+    "warmup_steps": 100,
+    "total_timesteps": 10000,
+    "weight_decay": 0.0001,
+    "max_grad_norm": 1.0,
+    "q_value_clip": 100.0,
+    "normalize_rewards": true,
+    "cost_bps": 10,
+    "cash_buffer": 0.02,
+    "max_position_weight": 0.2,
+    "reward_scale": 1.0,
+    "n_stocks": 15,
+    "seed": 42,
+    "validation_years": 2,
+    "min_cagr_improvement": 0.0,
+    "sharpe_weight": 0.5,
+    "sharpe_eta": 0.01,
+    "training_years": 10,
+    "n_eval_folds": 3
+  },
+  "promoted": true,
+  "prior_version": "v2026-01-30_a8b6fd41",
+  "metrics": {
+    "actor_loss": 0.47051061680353934,
+    "critic_loss": 0.0,
+    "avg_episode_return": 0.3164223983680193,
+    "avg_episode_sharpe": 0.23520403538043264,
+    "eval_sharpe": 1.239769458631745,
+    "eval_cagr": 0.302979570589738,
+    "eval_max_drawdown": 0.22627892173813877
+  }
 }

scaler.pkl

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symbol_order.json

@@ -1,6 +1,6 @@
 [
-  "AAPL",
   "NVDA",
+  "AAPL",
   "MSFT",
   "TSM",
   "GOOGL",
@@ -12,6 +12,5 @@
   "XOM",
   "JNJ",
   "TOELY",
-  "AMD",
-  "ABBV"
+  "MU"
 ]