README.md

metadata

library_name: peft
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
  - llama-factory
  - lora
  - generated_from_trainer
model-index:
  - name: Llama-3.1-8B-Instruct-QG-SFT
    results: []

Llama-3.1-8B-Instruct-QG-SFT

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the alpaca_en, the qg_sft, the wikiqa, the webqa and the openo1_sft datasets.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 6
• total_train_batch_size: 48
• total_eval_batch_size: 64
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• num_epochs: 1.0

Training results

Framework versions

• PEFT 0.12.0
• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0