gemma-2b-japaneseQA-instruct

This model is a fine-tuned version of google/gemma-2b 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: 0.0002
• train_batch_size: 3
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 6
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 3

Training results

Framework versions

• PEFT 0.7.2.dev0
• Transformers 4.38.0
• Pytorch 2.1.2+cu121
• Datasets 2.16.1
• Tokenizers 0.15.2