ucla-cmllab/llama-3-qlora-ultrachat-200k-processed-indicator-0.6

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

llama-3-qlora-ultrachat-200k-processed-indicator-0.6

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the yihanwang617/ultrachat200kprocessedindicator0.6_4k dataset. It achieves the following results on the evaluation set:

• —Loss: 1.0200

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: 0.0002
• —trainbatchsize: 2
• —evalbatchsize: 4
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 16
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 1

Training results

Framework versions

• —PEFT 0.12.0
• —Transformers 4.40.1
• —Pytorch 2.4.0+cu121
• —Datasets 2.20.0
• —Tokenizers 0.19.1