---
library_name: transformers
base_model: Ajayk/Truviz-ai-detect
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Truviz-ai-detect-new
  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. -->

# Truviz-ai-detect-new

This model is a fine-tuned version of [Ajayk/Truviz-ai-detect](https://huggingface.co/Ajayk/Truviz-ai-detect) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2677
- Accuracy: 0.9423

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3847        | 0.1   | 500  | 0.2306          | 0.9071   |
| 0.2661        | 0.2   | 1000 | 0.4132          | 0.8855   |
| 0.2539        | 0.3   | 1500 | 0.2856          | 0.9146   |
| 0.2548        | 0.4   | 2000 | 0.2069          | 0.9295   |
| 0.1454        | 0.5   | 2500 | 0.3659          | 0.9212   |
| 0.2236        | 0.6   | 3000 | 0.2453          | 0.9344   |
| 0.2285        | 0.7   | 3500 | 0.1480          | 0.9497   |
| 0.2007        | 0.8   | 4000 | 0.2612          | 0.9229   |
| 0.2503        | 0.9   | 4500 | 0.2008          | 0.9384   |
| 0.2128        | 1.0   | 5000 | 0.1633          | 0.953    |
| 0.0849        | 1.1   | 5500 | 0.2167          | 0.9538   |
| 0.0706        | 1.2   | 6000 | 0.3862          | 0.9347   |
| 0.0915        | 1.3   | 6500 | 0.2781          | 0.9487   |
| 0.1187        | 1.4   | 7000 | 0.2677          | 0.9423   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0