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katheryne

Easy Language Model Trainer

Let's benchmark GPUs LLM training with katheryne

Training settings - 7B Llama (100 steps)

Stage: Pretrain
Model: meta-llama/Llama-2-7b-hf
Dataset: bigscience-data/roots_zh-cn_wikipedia
per_device_train_batch_size: 2
accumulate_grad_batches: 1
max_seq_len: 512
max_steps: 100
gradient_checkpointing: true
dtype: bf16
lora: {"r": 16, "target_modules": ["q_proj", "v_proj"]}
GPU Time GPU Memory Memory Usage
NVIDIA L40S 00:38 48G 15,134MiB
NVIDIA RTX 6000 ada Generation 00:38 48G 15,134MiB
NVIDIA A800 80GB PCIe 00:41 80G 14,850MiB
NVIDIA A100 40GB PCIe 00:44 40G 14,863MiB
NVIDIA GeForce RTX 4090 01:02 24G 15,078MiB
Iluvatar BI-V150 01:09 32G 22,798MiB
NVIDIA RTX A6000 01:13 48G 14,944MiB
NVIDIA A40 01:16 48G 15,809MiB
NVIDIA GeForce RTX 3090 01:36 24G 14,928MiB

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Language Model Training and Inference Benchmark

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