lerobot/lerobot/configs/policy/hilserl_classifier.yaml

50 lines
1.2 KiB
YAML

# @package _global_
defaults:
- _self_
seed: 13
dataset_repo_id: aractingi/push_green_cube_hf_cropped_resized
train_split_proportion: 0.8
# Required by logger
env:
name: "classifier"
task: "binary_classification"
training:
num_epochs: 5
batch_size: 16
learning_rate: 1e-4
num_workers: 4
grad_clip_norm: 10
use_amp: true
log_freq: 1
eval_freq: 1 # How often to run validation (in epochs)
save_freq: 1 # How often to save checkpoints (in epochs)
save_checkpoint: true
# image_keys: ["observation.images.top", "observation.images.wrist"]
image_keys: ["observation.images.laptop", "observation.images.phone"]
label_key: "next.reward"
eval:
batch_size: 16
num_samples_to_log: 30 # Number of validation samples to log in the table
policy:
name: "hilserl/classifier/push_green_cube_hf_cropped_resized" #"hilserl/classifier/pick_place_lego_cube_1"
model_name: "facebook/convnext-base-224"
model_type: "cnn"
num_cameras: 2 # Has to be len(training.image_keys)
wandb:
enable: false
project: "classifier-training"
job_name: "classifier_training_0"
disable_artifact: false
device: "mps"
resume: false
output_dir: "outputs/classifier"