---
license: gemma
base_model: google/gemma-2-9b-it
tags:
- generated_from_trainer
model-index:
- name: gemma-2-9b-it-lora-commonsense
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yspkm/PrunePath-LoRA/runs/8piyty9j)
# gemma-2-9b-it-lora-commonsense

This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8229

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0188        | 0.1503 | 200  | 0.9641          |
| 0.9971        | 0.3007 | 400  | 0.9404          |
| 0.9827        | 0.4510 | 600  | 0.9288          |
| 0.9748        | 0.6013 | 800  | 0.9194          |
| 0.971         | 0.7516 | 1000 | 0.9055          |
| 0.957         | 0.9020 | 1200 | 0.8970          |
| 0.9005        | 1.0523 | 1400 | 0.8874          |
| 0.8876        | 1.2026 | 1600 | 0.8748          |
| 0.8782        | 1.3529 | 1800 | 0.8640          |
| 0.8896        | 1.5033 | 2000 | 0.8489          |
| 0.8814        | 1.6536 | 2200 | 0.8417          |
| 0.8666        | 1.8039 | 2400 | 0.8325          |
| 0.8674        | 1.9542 | 2600 | 0.8307          |
| 0.8116        | 2.1046 | 2800 | 0.8366          |
| 0.8032        | 2.2549 | 3000 | 0.8291          |
| 0.8103        | 2.4052 | 3200 | 0.8265          |
| 0.8165        | 2.5556 | 3400 | 0.8245          |
| 0.8085        | 2.7059 | 3600 | 0.8242          |
| 0.8121        | 2.8562 | 3800 | 0.8229          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1