lora_eager_ko-gemma-2-9b-it_nqa-sft-dataset

This model is a fine-tuned version of rtzr/ko-gemma-2-9b-it on the generator dataset.

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-07
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 8
• total_eval_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Framework versions

• PEFT 0.12.0
• Transformers 4.45.2
• Pytorch 2.4.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3