Datasets:

mateoguaman
/

vamos_50pct_traj_25pct_atraj_25pct_anno

lang_goal stringlengths 47 49	trajectory_2d listlengths 1 480	trajectory_3d listlengths 1 480	camera_params stringclasses 4 values	horizon int64 1 480	shorter_trajectory_2d listlengths 1 472	shorter_trajectory_3d listlengths 1 472	subsampled_trajectory_2d listlengths 5 5	goal_2d listlengths 2 2	text stringlengths 36 36	label stringlengths 90 90	label_list listlengths 5 5	curvature float64 1 30
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vamos_50pct_traj_25pct_atraj_25pct_anno

Description

VLN Navigation dataset with 100% of tartandrive data, 50% of scand data, 25% of coda data, 100% of in-domain spot data, and 10% of annotated/augmented data using gpt5-mini. Whenever daatsets aren't 100%, they are ranked by curvature and output of length 5.

Processing Parameters

{}

Dataset Configuration

Train dataset:
  mixer: mateoguaman/annotations_only_10pct_gpt5_mini: 0.25
mateoguaman/vlmn_tartandrive100_scand50_coda25_spot100_sub5: 0.5
mateoguaman/vlmn_tartandrive100_scand50_coda25_spot100_sub5_filtered_trajectories_training_10_fixed: 0.25

  split: train
  
Validation dataset:
  mixer: mateoguaman/annotations_only_10pct_gpt5_mini: 0.25
mateoguaman/vlmn_tartandrive100_scand50_coda25_spot100_sub5: 0.5
mateoguaman/vlmn_tartandrive100_scand50_coda25_spot100_sub5_filtered_trajectories_training_10_fixed: 0.25

  split: validation

Additional Information

This dataset was created by consolidating cached processed datasets from the VLM Navigation project.

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Models trained or fine-tuned on mateoguaman/vamos_50pct_traj_25pct_atraj_25pct_anno

mateoguaman/paligemma2-3b-pt-224-sft-lora-vamos_50pct_traj_25pct_atraj_25pct_anno

Image-Text-to-Text • Updated Sep 15, 2025 • 2