---
library_name: transformers
license: llama3.1
base_model: meta-llama/Llama-3.1-8B
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: zephyr-8b-sft-full
  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. -->

# zephyr-8b-sft-full

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0747

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.103         | 0.1052 | 100  | 1.0989          |
| 1.0867        | 0.2103 | 200  | 1.0966          |
| 1.111         | 0.3155 | 300  | 1.1012          |
| 1.0974        | 0.4206 | 400  | 1.0966          |
| 1.0898        | 0.5258 | 500  | 1.0920          |
| 1.0749        | 0.6309 | 600  | 1.0876          |
| 1.0847        | 0.7361 | 700  | 1.0831          |
| 1.0749        | 0.8412 | 800  | 1.0778          |
| 1.055         | 0.9464 | 900  | 1.0720          |
| 0.9184        | 1.0515 | 1000 | 1.0817          |
| 0.8955        | 1.1567 | 1100 | 1.0779          |
| 0.914         | 1.2618 | 1200 | 1.0758          |
| 0.9098        | 1.3670 | 1300 | 1.0698          |
| 0.9126        | 1.4721 | 1400 | 1.0667          |
| 0.9032        | 1.5773 | 1500 | 1.0604          |
| 0.8882        | 1.6824 | 1600 | 1.0546          |
| 0.8847        | 1.7876 | 1700 | 1.0490          |
| 0.8831        | 1.8927 | 1800 | 1.0455          |
| 0.8781        | 1.9979 | 1900 | 1.0413          |
| 0.7197        | 2.1030 | 2000 | 1.0822          |
| 0.7137        | 2.2082 | 2100 | 1.0841          |
| 0.7115        | 2.3134 | 2200 | 1.0800          |
| 0.7178        | 2.4185 | 2300 | 1.0789          |
| 0.7063        | 2.5237 | 2400 | 1.0777          |
| 0.6964        | 2.6288 | 2500 | 1.0755          |
| 0.7121        | 2.7340 | 2600 | 1.0742          |
| 0.7049        | 2.8391 | 2700 | 1.0748          |
| 0.7024        | 2.9443 | 2800 | 1.0747          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.2.2+rocm5.7
- Datasets 3.2.0
- Tokenizers 0.20.3