AI 와 빅데이터 분석 전문 기업인 Linkbricks의 데이터사이언티스트인 지윤성 박사(Saxo)가 beomi/llama-2-koen-13b 베이스모델을 GCP상의 A100-40G 4개를 통해 SFT 훈련을 한(2048 Tokens) 인스트럭션 모델. Accelerate, Deepspeed Zero-3 라이브러리를 사용했으며 Flash Attention 은 Disable 로 설정

Dr. Yunsung Ji (Saxo), a data scientist at Linkbricks, a company specializing in AI and big data analytics, trained the beomi/llama-2-koen-13b base model on 4 A100-40Gs on GCP for 4 hours of instructional training (2048 Tokens). Accelerate, Deepspeed Zero-3 libraries were used.

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Configuration including BitsandBytes

learning_rate = 2e-4 num_epochs = 5 batch_size = 4 block_size = 2048 trainer = "sft" warmup_ratio = 0.1 weight_decay = 0.01 gradient_accumulation = 4 mixed_precision = "fp16" peft = True quantization = "int4" lora_r = 64 lora_alpha = 16 lora_dropout = 0.1 model_max_length = 2048

Dataset Format

Alpaca Format Prompt Text

Saxo/yunsung-llama-2-koen-13b-linkbricks-sft-basic-v1

Model Card for Model ID

Configuration including BitsandBytes

learning_rate = 2e-4 num_epochs = 5 batch_size = 4 block_size = 2048 trainer = "sft" warmup_ratio = 0.1 weight_decay = 0.01 gradient_accumulation = 4 mixed_precision = "fp16" peft = True quantization = "int4" lora_r = 64 lora_alpha = 16 lora_dropout = 0.1 model_max_length = 2048

Dataset Format

Saxo/
yunsung-llama-2-koen-13b-linkbricks-sft-basic-v1