README.md

---
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: llama-ai-detect-v3-test-vastai
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama-ai-detect-v3-test-vastai

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: 0.7499
- Accuracy: 0.7
- Precision: 0.7143
- Recall: 0.8333
- F1: 0.7692

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 1    | 1.0919          | 0.6      | 0.6667    | 0.6667 | 0.6667 |
| No log        | 2.0   | 2    | 0.9340          | 0.7      | 0.7143    | 0.8333 | 0.7692 |
| No log        | 3.0   | 3    | 0.8300          | 0.7      | 0.7143    | 0.8333 | 0.7692 |
| No log        | 4.0   | 4    | 0.7732          | 0.7      | 0.7143    | 0.8333 | 0.7692 |
| No log        | 5.0   | 5    | 0.7499          | 0.7      | 0.7143    | 0.8333 | 0.7692 |


### Framework versions

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