Edit model card

基于ruozhiba对Llama-3-8B-Instruct进行微调。

模型:

数据集:

训练工具

https://github.com/hiyouga/LLaMA-Factory

测评方式:

使用opencompass(https://github.com/open-compass/OpenCompass/ ), 测试工具基于CEval和MMLU对微调之后的模型和原始模型进行测试。
测试模型分别为:

  • Llama-3-8B
  • Llama-3-8B-Instruct
  • LLama3-Instruct-sft-ruozhiba,使用ruozhiba数据对Llama-3-8B-Instruct使用sft方式lora微调

结果

模型名称 CEVAL MMLU
LLama3 49.91 66.62
LLama3-Instruct 50.55 67.15
LLama3-Instruct-sft-ruozhiba-3epoch 50.87 67.51

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 20
  • num_epochs: 3.0
  • mixed_precision_training: Native AMP
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model's library. Check the docs .

Dataset used to train REILX/Llama-3-8B-Instruct-ruozhiba-lora

Collection including REILX/Llama-3-8B-Instruct-ruozhiba-lora