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lerobot/lerobot/configs/policy/hilserl_classifier.yaml
Yoel e35546f58e Reward classifier and training (#528)
Co-authored-by: Daniel Ritchie <daniel@brainwavecollective.ai>
Co-authored-by: resolver101757 <kelster101757@hotmail.com>
Co-authored-by: Jannik Grothusen <56967823+J4nn1K@users.noreply.github.com>
Co-authored-by: Remi <re.cadene@gmail.com>
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
2024-12-17 02:41:29 +07:00

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YAML

# @package _global_
defaults:
- _self_
seed: 13
dataset_repo_id: "dataset_repo_id"
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_key: "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"
model_name: "facebook/convnext-base-224"
model_type: "cnn"
wandb:
enable: false
project: "classifier-training"
entity: "wandb_entity"
job_name: "classifier_training_0"
disable_artifact: false
device: "mps"
resume: false
output_dir: "output"