---
license: apache-2.0
tags:
  - autonomous-driving
  - alpamayo
  - baseline
---
# Alpamayo R1 — BL (10k-only) baseline

3-epoch SFT of `Alpamayo-R1-10B` on the **pure 10k random NV subset** — no
OOD-train labels, no Ray-WAN synth. This is the no-augmentation baseline
that anchors the BL / GT-oracle / Ours-synth long-tail comparison.

- **Backbone**: `Alpamayo-R1-10B`
- **Data**: `alpamayo_synth_longtail/alpamayo_bl_v1` (10k random clips, 4-cam NV slots [0,1,2,6])
- **Schedule**: Stage 1 (token CE) → Stage 2 (flow matching diffusion expert), 3 epochs each
- **Final Stage 2 train_loss**: 0.24 (3750 global steps, 1250 steps/epoch × 3)

## Files

- `model-*-of-*.safetensors`: model weights (~21 GB total)
- `model.safetensors.index.json`: shard index
- `config.json`: model config
- `trainer_state.json`: full training history
- `training_args.bin`, `scheduler.pt`: trainer state

Optimizer states are NOT included (only useful for training resume).

## Loading

```python
from alpamayo_r1.models.alpamayo_r1 import AlpamayoR1
model = AlpamayoR1.from_pretrained("luuuulinnnn/alpamyo_BL")
```

## Companion repos

- `luuuulinnnn/alpamyo_Waymo` — R-A / R-B / R-C trio (Waymo-component variants)