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---
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
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