---
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- nthakur/mirage-meta-llama-3-sft-instruct
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct
  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. -->

# Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the nthakur/mirage-meta-llama-3-sft-instruct dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2431

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3403        | 0.0597 | 200  | 0.3074          |
| 0.3224        | 0.1195 | 400  | 0.2954          |
| 0.3055        | 0.1792 | 600  | 0.2886          |
| 0.2899        | 0.2389 | 800  | 0.2804          |
| 0.3116        | 0.2987 | 1000 | 0.2772          |
| 0.3101        | 0.3584 | 1200 | 0.2728          |
| 0.2913        | 0.4182 | 1400 | 0.2679          |
| 0.2765        | 0.4779 | 1600 | 0.2625          |
| 0.2697        | 0.5376 | 1800 | 0.2601          |
| 0.2759        | 0.5974 | 2000 | 0.2557          |
| 0.264         | 0.6571 | 2200 | 0.2524          |
| 0.2705        | 0.7168 | 2400 | 0.2490          |
| 0.2694        | 0.7766 | 2600 | 0.2466          |
| 0.2639        | 0.8363 | 2800 | 0.2450          |
| 0.2598        | 0.8961 | 3000 | 0.2435          |
| 0.2483        | 0.9558 | 3200 | 0.2432          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1