---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- trl-lib/kto-mix-14k
- chaoweihuang/lf-response-llama3-f1_100_0.8-fg0.5
model-index:
- name: kto-mix-14k-lf-response-llama3-f1_100_0.8-fg0.5-fgudw4.0-kto-fg
  results: []
---

# FactAlign-LLaMA-3-8B
This model is aligned with our **FactAlign** framework for improved long-form factuality, from [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct).

For more information, please refer to our paper: [FactAlign: Long-form Factuality Alignment of Large Language Models](https://huggingface.co./papers/2410.01691).


## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data


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 trl-lib/kto-mix-14k and the chaoweihuang/lf-response-llama3-f1_100_0.8-fg0.5 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4110
- Rewards/chosen: 1.7360
- Logps/chosen: -336.0412
- Rewards/rejected: -2.2628
- Logps/rejected: -406.1173
- Rewards/margins: 3.9987
- Kl: 0.0141
- Fg Rewards/chosen Sum: -1.5560
- Fg Logps/policy Chosen: -6.7332
- Fg Logps/reference Chosen: -6.0419
- Count/fg Chosen: 30.1832
- Fg Rewards/rejected Sum: -0.9033
- Fg Logps/policy Rejected: -8.6269
- Fg Logps/reference Rejected: -7.5807
- Count/fg Rejected: 6.9239
- Fg Logps/policy Kl: -14.7946
- Fg Logps/reference Kl: -11.4736
- Fg Kl: nan
- Fg Loss: 0.7625


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Logps/chosen | Rewards/rejected | Logps/rejected | Rewards/margins | Kl     | Fg Rewards/chosen Sum | Fg Logps/policy Chosen | Fg Logps/reference Chosen | Count/fg Chosen | Fg Rewards/rejected Sum | Fg Logps/policy Rejected | Fg Logps/reference Rejected | Count/fg Rejected | Fg Logps/policy Kl | Fg Logps/reference Kl | Fg Kl | Fg Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---------------:|:------:|:---------------------:|:----------------------:|:-------------------------:|:---------------:|:-----------------------:|:------------------------:|:---------------------------:|:-----------------:|:------------------:|:---------------------:|:-----:|:-------:|
| 0.4478        | 0.4103 | 400  | 0.4325          | 1.3169         | -340.2313    | -1.7364          | -400.8539      | 3.0534          | 0.0280 | -1.3939               | -6.6287                | -6.0419                   | 30.1832         | -0.6768                 | -8.3632                  | -7.5807                     | 6.9239            | -13.6783           | -11.4736              | nan   | 0.7654  |
| 0.4043        | 0.8205 | 800  | 0.4110          | 1.7360         | -336.0412    | -2.2628          | -406.1173      | 3.9987          | 0.0141 | -1.5560               | -6.7332                | -6.0419                   | 30.1832         | -0.9033                 | -8.6269                  | -7.5807                     | 6.9239            | -14.7946           | -11.4736              | nan   | 0.7625  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1