---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: outputs
  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. -->

# outputs

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8215
- Model Preparation Time: 0.0166

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|
| 2.1179        | 1.1765 | 20   | 2.0786          | 0.0166                 |
| 1.1724        | 2.3529 | 40   | 1.2198          | 0.0166                 |
| 0.9532        | 3.5294 | 60   | 0.9806          | 0.0166                 |
| 0.851         | 4.7059 | 80   | 0.8941          | 0.0166                 |
| 0.8294        | 5.8824 | 100  | 0.8571          | 0.0166                 |
| 0.7754        | 7.0588 | 120  | 0.8378          | 0.0166                 |
| 0.748         | 8.2353 | 140  | 0.8258          | 0.0166                 |
| 0.7357        | 9.4118 | 160  | 0.8224          | 0.0166                 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2
- Datasets 2.21.0
- Tokenizers 0.19.1