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akoksal avatar akoksal commented on June 3, 2024

I use generic autoregressive model finetuning from HuggingFace trainer with the following tricks:

  • Group texts with this function with the block size of 1024.
  • Include end-of-instruction ([EOI]) token at the end of the input/instruction to clarify the separation between input and output.
  • Calcluate the loss for the whole part: input and output.
  • Most importantly I'm using the following DeepSpeed config for the optimizations and set it in the HuggingFace trainer (I enabled bf16 optimization in the HuggingFace trainer):
{
    "fp16": {
        "enabled": "auto",
        "loss_scale": 0,
        "loss_scale_window": 1000,
        "initial_scale_power": 16,
        "hysteresis": 2,
        "min_loss_scale": 1
    },

    "bf16": {
        "enabled": "auto"
    },

    "optimizer": {
        "type": "AdamW",
        "params": {
            "lr": "auto",
            "betas": "auto",
            "eps": "auto",
            "weight_decay": "auto"
        }
    },

    "scheduler": {
        "type": "WarmupLR",
        "params": {
            "warmup_min_lr": "auto",
            "warmup_max_lr": "auto",
            "warmup_num_steps": "auto"
        }
    },

    "zero_optimization": {
        "stage": 3,
        "offload_optimizer": {
            "device": "cpu",
            "pin_memory": true
        },
        "allgather_bucket_size": 2e8,
        "overlap_comm": true,
        "contiguous_gradients": true,
        "sub_group_size": 1e12,
        "reduce_bucket_size": 2e8,
        "stage3_prefetch_bucket_size": "auto",
        "stage3_param_persistence_threshold": "auto",
        "stage3_max_live_parameters": 1e9,
        "stage3_max_reuse_distance": 1e9,
        "stage3_gather_16bit_weights_on_model_save": true
    },
    
    "gradient_accumulation_steps": "auto",
    "gradient_clipping": "auto",
    "steps_per_print": 50,
    "train_batch_size": "auto",
    "train_micro_batch_size_per_gpu": "auto",
    "wall_clock_breakdown": false
}

Hope it would help!

from longform.

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