---
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-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. -->

# gemma-ai-detect-v1

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: 0.1378
- Accuracy: 0.9612
- F1: 0.9689
- Precision: 0.9700
- Recall: 0.9678

## 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: 0.0006
- train_batch_size: 192
- eval_batch_size: 192
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 209  | 0.1632          | 0.9322   | 0.9472 | 0.9214    | 0.9745 |
| No log        | 2.0   | 418  | 0.1209          | 0.9524   | 0.9617 | 0.9665    | 0.9569 |
| 0.2181        | 3.0   | 627  | 0.1280          | 0.9512   | 0.9608 | 0.9627    | 0.9590 |
| 0.2181        | 4.0   | 836  | 0.1378          | 0.9612   | 0.9689 | 0.9700    | 0.9678 |


### Framework versions

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