---
language:
- en
library_name: lerobot
license: gemma
pipeline_tag: robotics
tags:
- vision-language-action
- imitation-learning
- behavior-cloning
- lerobot
- pi05
- pi0.5
- openpi
- robotics
- isaaclab
- so101
- multi-task
- corl2026
- bfloat16
- full-finetune
- safetensors
datasets:
- CoRL2026-CSI/Isaaclab-so101_11task_baseCaP_3300epi
base_model:
- lerobot/pi05_base
inference: false
---

# Pi0.5 IsaacLab Multi-Task 1 Epoch

This repository contains a Pi0.5 policy fine-tuned with LeRobot on the IsaacLab SO-101 multi-task dataset `CoRL2026-CSI/Isaaclab-so101_11task_baseCaP_3300epi`.

## Model Details

- **Base model:** `lerobot/pi05_base`
- **Policy type:** `pi05`
- **Training type:** full fine-tuning
- **Vision encoder frozen:** no
- **Action expert only:** no
- **Checkpoint:** final checkpoint at step `13761`
- **Training length:** `1.00` epoch
- **Precision:** bfloat16
- **Format:** safetensors

## Dataset

- **Dataset:** `CoRL2026-CSI/Isaaclab-so101_11task_baseCaP_3300epi`
- **Robot:** SO-101 follower
- **Episodes:** `3300`
- **Frames:** `3,522,774`
- **Tasks:** `800`
- **FPS:** `30`
- **Visual inputs:** `observation.images.top`, `observation.images.left_wrist`
- **State/action dimensions:** 6 DoF robot state/action, padded by the Pi0.5 policy configuration as needed

## Training Hyperparameters

| Setting | Value |
|---|---:|
| Steps | `13761` |
| Epochs | `1.00` |
| Per-device batch size | `16` |
| GPUs | `2` |
| Gradient accumulation | `8` |
| Effective batch size | `256` |
| Mixed precision | `bf16` |
| Policy dtype | `bfloat16` |
| Chunk size | `16` |
| Action steps | `16` |
| Gradient checkpointing | `true` |
| Compile model | `false` |
| DataLoader workers | `8` |
| DataLoader prefetch factor | `2` |
| Persistent workers | `true` |
| Pin memory | `true` |
| Preprocess in workers | `true` |
| DDP find unused parameters | `true` |
| Seed | `1000` |

### Optimizer and Scheduler

| Setting | Value |
|---|---:|
| Optimizer | AdamW |
| Learning rate | `2.5e-5` |
| Betas | `[0.9, 0.95]` |
| Epsilon | `1e-8` |
| Weight decay | `0.01` |
| Gradient clip norm | `1.0` |
| Scheduler | cosine decay with warmup |
| Configured warmup steps | `1000` |
| Effective warmup steps | `458` |
| Configured decay steps | `30000` |
| Effective decay steps | `13761` |
| Final decay LR | `2.5e-6` |

The scheduler was automatically scaled because `num_training_steps=13761` was smaller than the configured `num_decay_steps=30000`.

## Final Training Log Snapshot

The final logged training metrics near completion were:

- `step=13760/13761`
- `epoch=1.00`
- `loss=0.009`
- `grad_norm=0.259`
- `lr=2.5e-06`
- `updt_s=1.658`
- `data_s=0.017`

Training completed successfully on `2026-05-13 18:37:47 UTC`.

## Files

This repository includes only the inference/evaluation policy files from `pretrained_model`:

- `config.json`
- `model.safetensors`
- `train_config.json`
- `policy_preprocessor.json`
- `policy_preprocessor_step_2_normalizer_processor.safetensors`
- `policy_postprocessor.json`
- `policy_postprocessor_step_0_unnormalizer_processor.safetensors`

Optimizer state and other resumable training-state files are intentionally excluded.

## Evaluation Status

No rollout or task-success evaluation metrics are included yet. This checkpoint is intended as a reproducible 1-epoch Pi0.5 fine-tuning artifact for IsaacLab SO-101 multi-task experiments.

## Reproducibility

Training was launched from the AutoDataCollector LeRobot workspace using the Pi0.5 IsaacLab training script configuration corresponding to:

```bash
DATASET_REPO_ID=CoRL2026-CSI/Isaaclab-so101_11task_baseCaP_3300epi POLICY_PATH=lerobot/pi05_base BATCH_SIZE=16 GRADIENT_ACCUMULATION_STEPS=8 NUM_GPUS=2 STEPS=13761 MIXED_PRECISION=bf16 POLICY_DTYPE=bfloat16 CHUNK_SIZE=16 N_ACTION_STEPS=16 GRADIENT_CHECKPOINTING=true FREEZE_VISION_ENCODER=false TRAIN_EXPERT_ONLY=false NUM_WORKERS=8 DATALOADER_PREFETCH_FACTOR=2 DATALOADER_PERSISTENT_WORKERS=true DATALOADER_PIN_MEMORY=true PREPROCESS_IN_WORKERS=true OPTIMIZER_LR=2.5e-5 OPTIMIZER_WEIGHT_DECAY=0.01 OPTIMIZER_GRAD_CLIP_NORM=1.0 SCHEDULER_WARMUP_STEPS=1000 SCHEDULER_DECAY_STEPS=30000 SCHEDULER_DECAY_LR=2.5e-6 ./lerobot/scripts/train_pi05_isaaclab.sh
```