This model is a fine-tuned version of huggyllama/llama-7b on on openassistant-guanaco dataset. For LoraConfig we set the use_dora=True for the Dora decomposition and comparison with Lora.

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: 0.0003
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

ShirinYamani/huggyllama-llama-7b-finetuned

llama-3-8-fine-tuned-dora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ShirinYamani/
huggyllama-llama-7b-finetuned