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README.md

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+---
+license: apache-2.0
+datasets:
+- lerobot/pusht
+---
 # Model Card for Diffusion Policy / PushT
 
 Diffusion Policy (as per [Diffusion Policy: Visuomotor Policy
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 ## Training Details
 
-TODO commit hash.
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-Trained with [LeRobot@d747195](https://github.com/huggingface/lerobot/tree/d747195c5733c4f68d4bfbe62632d6fc1b605712).
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 The model was trained using [LeRobot's training script](https://github.com/huggingface/lerobot/blob/d747195c5733c4f68d4bfbe62632d6fc1b605712/lerobot/scripts/train.py) and with the [pusht](https://huggingface.co/datasets/lerobot/pusht/tree/v1.3) dataset.
 
 Here are the [loss](./train_loss.csv), [evaluation score](./eval_avg_max_reward.csv), [evaluation success rate](./eval_pc_success.csv) (with 50 rollouts) during training.
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 This took about 7 hours to train on an Nvida RTX 3090.
 
+_Note: At the time of training, [this PR](https://github.com/huggingface/lerobot/pull/129) was also incorporated._
+
 ## Evaluation
 
 The model was evaluated on the `PushT` environment from [gym-pusht](https://github.com/huggingface/gym-pusht) and compared to a similar model trained with the original [Diffusion Policy code](https://github.com/real-stanford/diffusion_policy). There are two evaluation metrics on a per-episode basis: