---
license: gemma
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-2b-it
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: gemma-ai-detect-v3-multilingual
  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-ai-detect-v3-multilingual

This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1267
- Accuracy: 0.9737
- F1: 0.9787
- Precision: 0.9802
- Recall: 0.9772

## 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: 56
- eval_batch_size: 56
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1048        | 1.0   | 1072 | 0.0781          | 0.9691   | 0.9751 | 0.9734    | 0.9767 |
| 0.0373        | 2.0   | 2144 | 0.0925          | 0.9701   | 0.9757 | 0.9817    | 0.9698 |
| 0.0073        | 3.0   | 3216 | 0.1267          | 0.9737   | 0.9787 | 0.9802    | 0.9772 |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.5.1+cu124
- Datasets 2.18.0
- Tokenizers 0.19.1