---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- hansh/hansken_hql
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: hansken_human_hql
  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. -->

# hansken_human_hql

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the hansh/hansken_hql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2362

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_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: 20

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4508        | 0.9976 | 102  | 0.4433          |
| 0.302         | 1.9951 | 204  | 0.3140          |
| 0.2692        | 2.9927 | 306  | 0.2616          |
| 0.177         | 4.0    | 409  | 0.2431          |
| 0.1616        | 4.9976 | 511  | 0.2362          |
| 0.1358        | 5.9951 | 613  | 0.2394          |
| 0.1199        | 6.9927 | 715  | 0.2474          |
| 0.1051        | 8.0    | 818  | 0.2625          |
| 0.0945        | 8.9976 | 920  | 0.2797          |
| 0.0843        | 9.9951 | 1022 | 0.2892          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1