初始化项目，由ModelHub XC社区提供模型

Model: mrsteamedbun/llama3-8B-Agent
Source: Original Platform

README.md

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+---
+frameworks:
+- Pytorch
+license: Apache License 2.0
+tasks:
+- text-generation
+
+#model-type:
+##如 gpt、phi、llama、chatglm、baichuan 等
+#- gpt
+
+#domain:
+##如 nlp、cv、audio、multi-modal
+#- nlp
+
+#language:
+##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
+#- cn 
+
+#metrics:
+##如 CIDEr、Blue、ROUGE 等
+#- CIDEr
+
+#tags:
+##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
+#- pretrained
+
+#tools:
+##如 vllm、fastchat、llamacpp、AdaSeq 等
+#- vllm
+---
+## Llama-3-8B-Agent
+This Adapter is fine-tune from [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) using [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
+
+### Environment
+LLaMA-Factory Commit Version: **db7f3b9784d21ef5c18a11679ad995bb97d61f7c**
+
+GPU RTX-4090 24G 单卡
+
+Python 310
+
+### Training hyperparameters
+**Please ensure [FA2](https://github.com/Dao-AILab/flash-attention) installed**
+
+```bash
+CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
+    --stage sft \
+    --do_train \
+    --model_name_or_path /data/models/Meta-Llama-3-8B-Instruct \
+    --dataset alpaca_gpt4_zh,glaive_toolcall \
+    --dataset_dir data \
+    --template llama3 \
+    --finetuning_type lora \
+    --lora_target all \
+    --output_dir saves/LLaMA3-8B/lora/sft \
+    --overwrite_cache \
+    --overwrite_output_dir \
+    --cutoff_len 8192 \
+    --preprocessing_num_workers 16 \
+    --per_device_train_batch_size 1 \
+    --per_device_eval_batch_size 2 \
+    --gradient_accumulation_steps 8 \
+    --lr_scheduler_type cosine \
+    --logging_steps 10 \
+    --warmup_steps 20 \
+    --save_steps 1000 \
+    --eval_steps 1000 \
+    --max_samples 6000 \
+    --evaluation_strategy steps \
+    --load_best_model_at_end \
+    --learning_rate 5e-6 \
+    --num_train_epochs 3.0 \
+    --val_size 0.1 \
+    --plot_loss \
+    --fp16 \
+    --flash_attn
+```
+
+### training loss
+
+![loss](training_loss.png)
+
+### example
+![example](example.png)