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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Meta-Llama-3-8B-Instruct-nomiracl-sft

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/nomiracl-instruct dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6358

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.6576        | 0.2981 | 200  | 1.6656          |
| 1.6447        | 0.5961 | 400  | 1.6409          |
| 1.6245        | 0.8942 | 600  | 1.6358          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1