surrogate-1 / configs /v2 /deepspeed-zero3.json
Ashira Pitchayapakayakul
feat(v1.5): 32B SFT config + 3-way benchmark (v1 vs base32B vs v1.5)
8056cbe
{
"_comment_purpose": "ZeRO-3 + CPU offload for 32B QLoRA on Kaggle T4Γ—2 (16GBΓ—2). Each T4 holds ~8GB sharded weights + LoRA grads. Optimizer states are paged to CPU RAM (Kaggle has 30GB).",
"bf16": {
"enabled": true
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
"eps": "auto",
"weight_decay": "auto"
}
},
"scheduler": {
"type": "WarmupDecayLR",
"params": {
"warmup_min_lr": "auto",
"warmup_max_lr": "auto",
"warmup_num_steps": "auto",
"total_num_steps": "auto"
}
},
"zero_optimization": {
"stage": 3,
"overlap_comm": true,
"contiguous_gradients": true,
"sub_group_size": 1000000000,
"reduce_bucket_size": "auto",
"stage3_prefetch_bucket_size": "auto",
"stage3_param_persistence_threshold": "auto",
"stage3_max_live_parameters": 1000000000,
"stage3_max_reuse_distance": 1000000000,
"stage3_gather_16bit_weights_on_model_save": true,
"offload_param": {
"device": "cpu",
"pin_memory": true
},
"offload_optimizer": {
"device": "cpu",
"pin_memory": true
}
},
"gradient_accumulation_steps": "auto",
"gradient_clipping": "auto",
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"wall_clock_breakdown": false
}