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@@ -75,7 +75,7 @@ For reproducibility, here are the key parameters used during this initial traini
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  - **Scheduler**: Cosine with warmup
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  - **Vision**: ResNet18 with random crop (84x84)
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- #### Original Training Command
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  ```bash
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  python -m lerobot.scripts.lerobot_train \
@@ -92,6 +92,18 @@ python -m lerobot.scripts.lerobot_train \
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  ## 🚀 Evaluate (My Evaluation Mode)
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  You can evaluate this checkpoint to reproduce the Phase 1 results:
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  ```bash
 
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  - **Scheduler**: Cosine with warmup
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  - **Vision**: ResNet18 with random crop (84x84)
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+ #### Original Training Command (My Training Mode)
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  ```bash
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  python -m lerobot.scripts.lerobot_train \
 
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  ## 🚀 Evaluate (My Evaluation Mode)
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+ Run the following command in your terminal to evaluate the model for 50 episodes and save the visualization videos:
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+
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+ ```bash
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+ python -m lerobot.scripts.lerobot_eval \
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+ --policy.type diffusion \
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+ --policy.pretrained_path outputs/train/2025-12-02/14-33-35_DP_PushT/checkpoints/last/pretrained_model \
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+ --eval.n_episodes 50 \
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+ --eval.batch_size 10 \
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+ --env.type pusht \
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+ --env.task PushT-v0
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+ ```
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+
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  You can evaluate this checkpoint to reproduce the Phase 1 results:
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  ```bash