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DeepSentinel GRPO Training
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[1] Collecting 120 training episodes...
    Collected 120 episodes
    Distribution: 40 easy, 40 medium, 40 hard

[2] Evaluating heuristic baseline...
    easy: avg_reward=-0.3681
    medium: avg_reward=0.0049
    hard: avg_reward=0.0833

[3] Loading model: Qwen/Qwen2.5-0.5B-Instruct

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The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None, 'pad_token_id': 151643}.
    Model loaded: 494.0M parameters

[4] Building training dataset...

[5] Configuring GRPO trainer...

[6] Training for 250 steps...
    Reward will be logged every 10 steps.
    Watch for increasing reward_mean over time.


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 40%|████      | 100/250 [58:08<1:27:33, 35.02s/it]{'loss': '-0.01747', 'grad_norm': '0', 'learning_rate': '1.928e-05', 'num_tokens': '6.185e+04', 'completions/mean_length': '362.8', 'completions/min_length': '318.1', 'completions/max_length': '379.3', 'completions/clipped_ratio': '0.8625', 'completions/mean_terminated_length': '46.41', 'completions/min_terminated_length': '38.1', 'completions/max_terminated_length': '57.8', 'rewards/reward_fn/mean': '-0.09879', 'rewards/reward_fn/std': '0.9303', 'reward': '-0.09879', 'reward_std': '0.9303', 'frac_reward_zero_std': '0.8', 'entropy': '0.5937', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '31.72', 'epoch': '0.3333'}
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{'loss': '-0.005067', 'grad_norm': '1.805', 'learning_rate': '1.768e-05', 'num_tokens': '1.915e+05', 'completions/mean_length': '396.2', 'completions/min_length': '369.7', 'completions/max_length': '400', 'completions/clipped_ratio': '0.975', 'completions/mean_terminated_length': '49.7', 'completions/min_terminated_length': '49.7', 'completions/max_terminated_length': '49.7', 'rewards/reward_fn/mean': '0.1105', 'rewards/reward_fn/std': '0.7119', 'reward': '0.1105', 'reward_std': '0.7119', 'frac_reward_zero_std': '0.9', 'entropy': '0.5579', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.49', 'epoch': '1'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '1.688e-05', 'num_tokens': '2.565e+05', 'completions/mean_length': '400', 'completions/min_length': '400', 'completions/max_length': '400', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.07887', 'rewards/reward_fn/std': '0.8938', 'reward': '0.07887', 'reward_std': '0.8938', 'frac_reward_zero_std': '0.95', 'entropy': '0.00434', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.44', 'epoch': '1.333'}
{'loss': '0', 'grad_norm': '0.3848', 'learning_rate': '1.608e-05', 'num_tokens': '3.211e+05', 'completions/mean_length': '395.1', 'completions/min_length': '360.9', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9875', 'completions/mean_terminated_length': '0.9', 'completions/min_terminated_length': '0.9', 'completions/max_terminated_length': '0.9', 'rewards/reward_fn/mean': '-0.1644', 'rewards/reward_fn/std': '1.064', 'reward': '-0.1644', 'reward_std': '1.064', 'frac_reward_zero_std': '0.975', 'entropy': '0.004431', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.56', 'epoch': '1.667'}
{'loss': '0.009756', 'grad_norm': '0', 'learning_rate': '1.528e-05', 'num_tokens': '3.848e+05', 'completions/mean_length': '385.5', 'completions/min_length': '283.7', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9625', 'completions/mean_terminated_length': '3.7', 'completions/min_terminated_length': '3.7', 'completions/max_terminated_length': '3.7', 'rewards/reward_fn/mean': '-0.1656', 'rewards/reward_fn/std': '0.936', 'reward': '-0.1656', 'reward_std': '0.936', 'frac_reward_zero_std': '0.925', 'entropy': '0.09349', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.49', 'epoch': '2'}
{'loss': '-0.01167', 'grad_norm': '2.406', 'learning_rate': '1.448e-05', 'num_tokens': '4.458e+05', 'completions/mean_length': '351.8', 'completions/min_length': '159.8', 'completions/max_length': '400', 'completions/clipped_ratio': '0.8625', 'completions/mean_terminated_length': '42.27', 'completions/min_terminated_length': '39.8', 'completions/max_terminated_length': '44.3', 'rewards/reward_fn/mean': '0.08913', 'rewards/reward_fn/std': '0.9902', 'reward': '0.08913', 'reward_std': '0.9902', 'frac_reward_zero_std': '0.925', 'entropy': '0.6014', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.48', 'epoch': '2.333'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '1.368e-05', 'num_tokens': '5.079e+05', 'completions/mean_length': '365.5', 'completions/min_length': '192.7', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9', 'completions/mean_terminated_length': '34.75', 'completions/min_terminated_length': '32.7', 'completions/max_terminated_length': '36.8', 'rewards/reward_fn/mean': '-0.1438', 'rewards/reward_fn/std': '0.6797', 'reward': '-0.1438', 'reward_std': '0.6797', 'frac_reward_zero_std': '0.975', 'entropy': '0.7648', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.44', 'epoch': '2.667'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '1.288e-05', 'num_tokens': '5.719e+05', 'completions/mean_length': '386.4', 'completions/min_length': '312.1', 'completions/max_length': '400', 'completions/clipped_ratio': '0.95', 'completions/mean_terminated_length': '35.4', 'completions/min_terminated_length': '32.1', 'completions/max_terminated_length': '38.7', 'rewards/reward_fn/mean': '-0.091', 'rewards/reward_fn/std': '0.7491', 'reward': '-0.091', 'reward_std': '0.7491', 'frac_reward_zero_std': '1', 'entropy': '0.8177', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.42', 'epoch': '3'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '1.208e-05', 'num_tokens': '6.358e+05', 'completions/mean_length': '386.5', 'completions/min_length': '292.1', 'completions/max_length': '400', 'completions/clipped_ratio': '0.95', 'completions/mean_terminated_length': '52.1', 'completions/min_terminated_length': '52.1', 'completions/max_terminated_length': '52.1', 'rewards/reward_fn/mean': '-0.1185', 'rewards/reward_fn/std': '0.978', 'reward': '-0.1185', 'reward_std': '0.978', 'frac_reward_zero_std': '1', 'entropy': '0.7871', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.45', 'epoch': '3.333'}


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100%|██████████| 250/250 [2:26:39<00:00, 35.17s/it]{'loss': '0', 'grad_norm': '0', 'learning_rate': '3.28e-06', 'num_tokens': '1.344e+06', 'completions/mean_length': '392.1', 'completions/min_length': '337.2', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9625', 'completions/mean_terminated_length': '57.2', 'completions/min_terminated_length': '57.2', 'completions/max_terminated_length': '57.2', 'rewards/reward_fn/mean': '-0.0115', 'rewards/reward_fn/std': '0.8286', 'reward': '-0.0115', 'reward_std': '0.8286', 'frac_reward_zero_std': '1', 'entropy': '0.913', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.59', 'epoch': '7'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '2.48e-06', 'num_tokens': '1.409e+06', 'completions/mean_length': '400', 'completions/min_length': '400', 'completions/max_length': '400', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.01825', 'rewards/reward_fn/std': '0.8384', 'reward': '0.01825', 'reward_std': '0.8384', 'frac_reward_zero_std': '1', 'entropy': '0.9604', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.32', 'epoch': '7.333'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '1.68e-06', 'num_tokens': '1.474e+06', 'completions/mean_length': '397.4', 'completions/min_length': '379.6', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9875', 'completions/mean_terminated_length': '19.6', 'completions/min_terminated_length': '19.6', 'completions/max_terminated_length': '19.6', 'rewards/reward_fn/mean': '-0.1123', 'rewards/reward_fn/std': '0.8594', 'reward': '-0.1123', 'reward_std': '0.8594', 'frac_reward_zero_std': '1', 'entropy': '0.9672', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.42', 'epoch': '7.667'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '8.8e-07', 'num_tokens': '1.538e+06', 'completions/mean_length': '389.5', 'completions/min_length': '316.1', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9625', 'completions/mean_terminated_length': '36.1', 'completions/min_terminated_length': '36.1', 'completions/max_terminated_length': '36.1', 'rewards/reward_fn/mean': '-0.015', 'rewards/reward_fn/std': '0.9199', 'reward': '-0.015', 'reward_std': '0.9199', 'frac_reward_zero_std': '1', 'entropy': '1.013', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.59', 'epoch': '8'}
{'loss': '0', 'grad_norm': '0', 'learning_rate': '8e-08', 'num_tokens': '1.603e+06', 'completions/mean_length': '391.8', 'completions/min_length': '334.6', 'completions/max_length': '400', 'completions/clipped_ratio': '0.9625', 'completions/mean_terminated_length': '54.6', 'completions/min_terminated_length': '54.6', 'completions/max_terminated_length': '54.6', 'rewards/reward_fn/mean': '0.0445', 'rewards/reward_fn/std': '0.861', 'reward': '0.0445', 'reward_std': '0.861', 'frac_reward_zero_std': '1', 'entropy': '0.9223', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'step_time': '33.55', 'epoch': '8.333'}


Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]

Writing model shards: 100%|██████████| 1/1 [00:05<00:00,  5.67s/it]
Writing model shards: 100%|██████████| 1/1 [00:05<00:00,  5.67s/it]

                                                   

100%|██████████| 250/250 [2:26:57<00:00, 35.17s/it]
100%|██████████| 250/250 [2:26:57<00:00, 35.27s/it]
{'train_runtime': '8818', 'train_samples_per_second': '0.227', 'train_steps_per_second': '0.028', 'train_loss': '-0.001472', 'epoch': '8.333'}

[7] Saving model to ./deepsentinel_model_small

Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
Writing model shards: 100%|██████████| 1/1 [00:07<00:00,  7.07s/it]
Writing model shards: 100%|██████████| 1/1 [00:07<00:00,  7.08s/it]
    Done!

[8] Post-training evaluation...
    Baseline vs Post-training (heuristic used for comparison):
    easy: -0.3681 → -0.3681 (Δ=+0.0000)
    medium: 0.0049 → 0.0049 (Δ=+0.0000)
    hard: 0.0833 → 0.0833 (Δ=+0.0000)

Training complete!
Model saved to: ./deepsentinel_model_small