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README.md

@@ -18,11 +18,7 @@ See the [LeRobot library](https://github.com/huggingface/lerobot) (particularly
 
 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.
-
-![](training_curves.png)
-
-This took about 7 hours to train on an Nvida RTX 3090.
+The training curves may be found at https://wandb.ai/alexander-soare/Alexander-LeRobot/runs/508luayd.
 
 _Note: At the time of training, [this PR](https://github.com/huggingface/lerobot/pull/129) was also incorporated._
 
@@ -40,3 +36,5 @@ Here are the metrics for 500 episodes worth of evaluation. For the succes rate w
 Average max. overlap ratio | 0.959 | 0.957
 Success rate for 500 episodes (%) | 63.8 | 64.2
 Beta distribution lower/mean/upper (%) | 61.6 / 63.7 / 65.9 | 62.0 / 64.1 / 66.3
+
+The results of each of the individual rollouts may be found in [eval_info.json](eval_info.json).