Baselines
Environment: hiyouga/verl:ngc-th2.6.0-cu126-vllm0.8.3-flashinfer0.2.2-cxx11abi0
EasyR1 version: v0.3.0
Welcome to contribute new data points!
Algorithm Baselines
Qwen2.5-Instruct on Math12k
| Size | Algorithm | Bits | LR | KL | Test Score |
|---|---|---|---|---|---|
| 7B | GRPO | AMP | 1e-6 | 1e-2 | 0.73->0.79 |
Qwen2.5-VL-Instruct on Geometry3k
| Size | Algorithm | Bits | LR | KL | Test Score |
|---|---|---|---|---|---|
| 7B | GRPO | AMP | 1e-6 | 1e-2 | 0.39->0.52 |
| 7B | GRPO | BF16 | 1e-6 | 1e-2 | 0.39->0.52 |
| 7B | GRPO | AMP | 1e-6 | 1e-3 | 0.39->0.52 |
| 7B | RLOO | AMP | 1e-6 | 1e-2 | 0.39->0.53 |
| 3B | GRPO | AMP | 1e-6 | 1e-2 | 0.27->0.44 |
| 32B | GRPO | BF16 | 1e-6 | 1e-2 | 0.46->0.61 |
The hyper-parameters not listed are all the same as the default values.
Performance Baselines
Qwen2.5-VL-Instruct on Geometry3k
| Size | GPU Type | Bits | Batch Size | vLLM Util | vLLM TP | Peak Mem | Peak VRAM | Throughput | Sec per step | Actor MFU |
|---|---|---|---|---|---|---|---|---|---|---|
| 3B | 8 * H100 80GB | AMP | 4 / 16 | 0.6 | 2 | 120GB | 35GB | 1200 | 180s | 6.3% |
| 7B | 8 * H100 80GB | AMP | 4 / 16 | 0.6 | 2 | 140GB | 60GB | 1200 | 180s | 13.6% |
| 7B | 8 * H100 80GB | AMP | 10 / 20 | 0.6 | 2 | 150GB | 75GB | 1400 | 170s | 19.2% |
| 7B | 8 * L20 48GB | AMP | 4 / 16 | 0.6 | 2 | 150GB | 44GB | 410 | 580s | 26.5% |
| 7B | 8 * H100 80GB | BF16 | 4 / 16 | 0.6 | 2 | 150GB | 50GB | 1280 | 190s | 13.9% |
| 32B | 8 * H100 80GB | BF16 | 1 / 8 | 0.6 | 8 | 240GB | 68GB | 360 | 860s | 11.2% |
- Batch Size: micro_batch_size_per_device_for_update / micro_batch_size_per_device_for_experience
- vLLM Util: rollout.gpu_memory_utilization
- vLLM TP: rollout.tensor_parallel_size
- Peak Mem: Peak CPU memory usage
- Peak VRAM: Peak GPU memory usage
- Throughput: Number of tokens per second per GPU by one training step
- Sec per step: Average time per step in seconds
The hyper-parameters not listed are all the same as the default values.