---
library_name: peft
license: gemma
base_model: google/gemma-3-27b-it
tags:
- base_model:adapter:google/gemma-3-27b-it
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: gemma-finetune-d1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gemma-finetune-d1

This model is a fine-tuned version of [google/gemma-3-27b-it](https://huggingface.co/google/gemma-3-27b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1715

## 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: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.709         | 0.4008 | 100  | 0.2020          |
| 1.4114        | 0.8016 | 200  | 0.1829          |
| 1.3051        | 1.2004 | 300  | 0.1783          |
| 1.2553        | 1.6012 | 400  | 0.1725          |
| 1.1126        | 2.0    | 500  | 0.1677          |
| 1.05          | 2.4008 | 600  | 0.1712          |
| 0.9771        | 2.8016 | 700  | 0.1715          |


### Framework versions

- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.22.1