gemma3n-lora-luna
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: 3.0176
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: 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: 50
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1416437.4 | 0.0893 | 100 | 3.0176 |
| 68800.2375 | 0.1785 | 200 | 3.0176 |
| 54955.675 | 0.2678 | 300 | 3.0176 |
| 140025.7625 | 0.3571 | 400 | 3.0176 |
| 206484.625 | 0.4463 | 500 | 3.0176 |
| 1362432.3 | 0.5356 | 600 | 3.0176 |
| 3724982.4 | 0.6249 | 700 | 3.0176 |
| 1319876.5 | 0.7141 | 800 | 3.0176 |
| 3529.084 | 0.8034 | 900 | 3.0176 |
| 1194336.8 | 0.8927 | 1000 | 3.0176 |
| 363691.15 | 0.9819 | 1100 | 3.0176 |
Framework versions
- PEFT 0.18.1
- Transformers 4.56.2
- Pytorch 2.9.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.2