---
base_model: google/gemma-2-9b-it
library_name: peft
license: gemma
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: gemma2_9b_LORA_Persian_MCQ_16_32_v1
  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. -->

# gemma2_9b_LORA_Persian_MCQ_16_32_v1

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: 0.8247

## 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: 4
- eval_batch_size: 4
- seed: 100
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1752        | 1.0   | 375  | 1.1416          |
| 0.8005        | 2.0   | 750  | 0.9006          |
| 0.6332        | 3.0   | 1125 | 0.8247          |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.44.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1