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---
base_model: google/gemma-2-9b
library_name: peft
license: gemma
tags:
- unsloth
- generated_from_trainer
model-index:
- name: gemma-2-9b_pct_reverse_r32
  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-2-9b_pct_reverse_r32

This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 9.9020

## 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: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.5978        | 0.0206 | 8    | 4.9799          |
| 11.0056       | 0.0412 | 16   | 11.4640         |
| 11.7215       | 0.0618 | 24   | 11.8765         |
| 11.8793       | 0.0824 | 32   | 11.9059         |
| 11.8739       | 0.1030 | 40   | 11.9781         |
| 11.8763       | 0.1236 | 48   | 11.9487         |
| 11.8231       | 0.1442 | 56   | 11.8282         |
| 11.7758       | 0.1648 | 64   | 11.7664         |
| 11.8011       | 0.1854 | 72   | 11.4372         |
| 11.6991       | 0.2060 | 80   | 11.7334         |
| 11.8108       | 0.2266 | 88   | 11.5005         |
| 11.6519       | 0.2472 | 96   | 11.5944         |
| 11.6905       | 0.2678 | 104  | 11.5944         |
| 11.6003       | 0.2885 | 112  | 11.5914         |
| 11.5813       | 0.3091 | 120  | 11.5684         |
| 11.5493       | 0.3297 | 128  | 11.7560         |
| 11.5458       | 0.3503 | 136  | 11.4566         |
| 11.5838       | 0.3709 | 144  | 11.4331         |
| 11.4815       | 0.3915 | 152  | 11.5174         |
| 11.5369       | 0.4121 | 160  | 11.5271         |
| 11.4617       | 0.4327 | 168  | 11.5392         |
| 11.4399       | 0.4533 | 176  | 11.3691         |
| 11.3199       | 0.4739 | 184  | 10.9823         |
| 10.6547       | 0.4945 | 192  | 10.0666         |
| 8.8163        | 0.5151 | 200  | 8.7638          |
| 9.5635        | 0.5357 | 208  | 8.5153          |
| 8.7862        | 0.5563 | 216  | 9.2186          |
| 10.2774       | 0.5769 | 224  | 10.3834         |
| 9.7932        | 0.5975 | 232  | 9.7972          |
| 9.5421        | 0.6181 | 240  | 9.6845          |
| 9.5401        | 0.6387 | 248  | 9.3438          |
| 10.9001       | 0.6593 | 256  | 10.6070         |
| 9.959         | 0.6799 | 264  | 9.6172          |
| 9.5409        | 0.7005 | 272  | 10.4762         |
| 10.8074       | 0.7211 | 280  | 10.4872         |
| 9.1645        | 0.7417 | 288  | 7.6567          |
| 8.1072        | 0.7623 | 296  | 8.7911          |
| 9.7069        | 0.7829 | 304  | 10.0043         |
| 10.0752       | 0.8035 | 312  | 10.1655         |
| 9.9734        | 0.8241 | 320  | 9.9644          |
| 9.6722        | 0.8447 | 328  | 9.7803          |
| 9.8279        | 0.8654 | 336  | 9.5826          |
| 9.6714        | 0.8860 | 344  | 9.5533          |
| 9.655         | 0.9066 | 352  | 9.6339          |
| 9.7184        | 0.9272 | 360  | 9.7651          |
| 9.6142        | 0.9478 | 368  | 9.8536          |
| 9.9249        | 0.9684 | 376  | 9.8906          |
| 9.8654        | 0.9890 | 384  | 9.9020          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1