---
license: apache-2.0
base_model: state-spaces/mamba2-370m
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: mamba2-370m
  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/truonggiabjnh2003-fpt-university/Detect%20AI%20Generated%20Text/runs/9ne43uyr)
# mamba2-370m

This model is a fine-tuned version of [state-spaces/mamba2-370m](https://huggingface.co/state-spaces/mamba2-370m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1239
- Accuracy: 0.9792
- Precision: 0.9795
- Recall: 0.9792
- F1: 0.9793
- Auroc: 0.9969

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- label_smoothing_factor: 0.03

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auroc  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.3764        | 0.1930 | 500  | 0.2099          | 0.9392   | 0.9385    | 0.9392 | 0.9375 | 0.9822 |
| 0.197         | 0.3861 | 1000 | 0.2205          | 0.9315   | 0.9462    | 0.9315 | 0.9344 | 0.9929 |
| 0.1748        | 0.5791 | 1500 | 0.1453          | 0.9690   | 0.9690    | 0.9690 | 0.9690 | 0.9942 |
| 0.1601        | 0.7721 | 2000 | 0.1352          | 0.9750   | 0.9756    | 0.9750 | 0.9752 | 0.9954 |
| 0.1542        | 0.9652 | 2500 | 0.2024          | 0.9428   | 0.9450    | 0.9428 | 0.9400 | 0.9935 |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.4.0+cu124
- Datasets 2.19.1
- Tokenizers 0.19.1