gemma3n-lora-luna-memory-distill-v2

This model is a fine-tuned version of unsloth/gemma-3n-e2b-it-unsloth-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: nan

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 3407
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_8BIT 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: 10
• training_steps: 30

Training results

Training Loss	Epoch	Step	Validation Loss
0.0	0.3125	20	nan

Framework versions

• PEFT 0.18.1
• Transformers 4.56.2
• Pytorch 2.9.0+cu126
• Datasets 4.3.0
• Tokenizers 0.22.2