File size: 3,507 Bytes
93f12cc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 | # Evaluation Scripts
Quick reference for running evaluations on Sokoban environment.
## Quick Start
### Evaluate Qwen 2.5 7B (Default)
```bash
# 128 trajectories, GPU 0
bash scripts/eval_qwen_7b_sokoban.sh
# 256 trajectories
bash scripts/eval_qwen_7b_sokoban.sh 256
# Custom GPU
bash scripts/eval_qwen_7b_sokoban.sh 128 1
```
**Output:** `outputs/qwen-2.5-7b-sokoban-128.jsonl`
### Evaluate Any Qwen Model
```bash
# General usage
bash scripts/eval_qwen_sokoban.sh <version> [num_traj] [gpu]
# Examples
bash scripts/eval_qwen_sokoban.sh 3B 128 0
bash scripts/eval_qwen_sokoban.sh 7B 256 1
bash scripts/eval_qwen_sokoban.sh 14B 128 0,1 # Multi-GPU
```
**Output:** `outputs/qwen-<version>-sokoban-<num>.jsonl`
### Batch Evaluation (All Models)
```bash
bash scripts/eval_batch.sh
```
Evaluates all Qwen models (0.5B, 1.5B, 3B, 7B, 14B) sequentially.
**Output:** Multiple files in `outputs/`
## Scripts Overview
### `eval_qwen_7b_sokoban.sh`
- **Purpose:** Quick eval for Qwen 2.5 7B Instruct
- **Args:** `[num_trajectories] [gpu_id]`
- **Default:** 128 trajectories on GPU 0
- **Output:** `outputs/qwen-2.5-7b-sokoban-{N}.jsonl`
### `eval_qwen_sokoban.sh`
- **Purpose:** Flexible eval for any Qwen model
- **Args:** `<model_version> [num_trajectories] [gpu_id]`
- **Versions:** 0.5B, 1.5B, 3B, 7B, 14B, 32B, 72B
- **Output:** `outputs/qwen-{version}-sokoban-{N}.jsonl`
### `eval_batch.sh`
- **Purpose:** Evaluate multiple models in sequence
- **Edit:** Modify `MODELS` array to customize model list
- **Output:** One JSONL per model in `outputs/`
## Output Format
All scripts output OpenAI-compatible JSONL:
```json
{
"custom_id": "traj_0",
"messages": [
{"role": "user", "content": "Grid state..."},
{"role": "assistant", "content": "<think>...</think><ans>up</ans>"},
{"role": "user", "content": "New grid... (reward: 0.0)"}
],
"metadata": {
"env_id": 0,
"success": true,
"total_reward": 1.0,
"num_turns": 5
}
}
```
## Common Configurations
### Trajectories
- **128:** Good for quick eval (8 groups × 16)
- **256:** Standard eval (16 groups × 16)
- **512:** Thorough eval (32 groups × 16)
The script auto-rounds to nearest multiple of 16.
### GPU Settings
- Single GPU: `0` or `1`
- Multi-GPU: `0,1` or `0,1,2,3`
### Model Sizes
| Model | VRAM | Recommended GPU |
|-------|------|-----------------|
| 0.5B | ~2GB | Any |
| 1.5B | ~4GB | RTX 3090 |
| 3B | ~8GB | RTX 3090 |
| 7B | ~16GB | A100 40GB |
| 14B | ~32GB | A100 80GB |
## Custom Evaluation
For full control, use the Python command directly:
```bash
python -m ragen.llm_agent.agent_proxy \
--config-name eval \
model_path="Qwen/Qwen2.5-7B-Instruct" \
system.CUDA_VISIBLE_DEVICES="0" \
es_manager.val.env_groups=8 \
es_manager.val.group_size=16 \
output.dir="outputs" \
output.filename="custom-name.jsonl" \
output.format=jsonl \
output.append_timestamp=false
```
## Troubleshooting
**Out of Memory:**
```bash
# Reduce context length in eval config
python -m ragen.llm_agent.agent_proxy --config-name eval \
actor_rollout_ref.rollout.max_model_len=2048 \
actor_rollout_ref.rollout.response_length=128
```
**Model not found:**
- Ensure model is downloaded or accessible via HuggingFace
- Check path format: `Qwen/Qwen2.5-{size}B-Instruct`
**Slow evaluation:**
- Use fewer trajectories for testing: `bash scripts/eval_qwen_7b_sokoban.sh 32`
- Enable greedy decoding: add `actor_rollout_ref.rollout.val_kwargs.temperature=0`
|