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---
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
should probably proofread and complete it, then remove this comment. -->
# 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 |