---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: sft-llama3-8b
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sft-llama3-8b

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0405

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0608        | 1.0   | 950  | 1.0696          |
| 0.9014        | 2.0   | 1900 | 1.0405          |
| 0.7183        | 3.0   | 2850 | 1.0691          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.3.0
- Datasets 2.14.6
- Tokenizers 0.15.2
