---
license: llama3
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: llama3-ai-detector-v3-20k-32batch-512max-len
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3-ai-detector-v3-20k-32batch-512max-len

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1170
- Accuracy: 0.9662
- Precision: 0.9865
- Recall: 0.9590
- F1: 0.9726

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3286        | 1.0   | 625  | 0.1242          | 0.9502   | 0.9842    | 0.9353 | 0.9591 |
| 0.1012        | 2.0   | 1250 | 0.1170          | 0.9662   | 0.9865    | 0.9590 | 0.9726 |
| 0.0543        | 3.0   | 1875 | 0.1445          | 0.9688   | 0.9717    | 0.9785 | 0.9751 |
| 0.0082        | 4.0   | 2500 | 0.1693          | 0.9688   | 0.9802    | 0.9696 | 0.9749 |
| 0.0015        | 5.0   | 3125 | 0.1849          | 0.9702   | 0.9784    | 0.9737 | 0.9761 |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1