---
library_name: transformers
license: llama3.2
base_model: tanliboy/llama-3.2-3b
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- tanliboy/OpenHermes-2.5-reformat
model-index:
- name: llama-3.2-3b-sft-2
  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. -->

# llama-3.2-3b-sft-2

This model is a fine-tuned version of [tanliboy/llama-3.2-3b](https://huggingface.co./tanliboy/llama-3.2-3b) on the tanliboy/OpenHermes-2.5-reformat dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6744

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.7792        | 0.0673 | 500   | 0.7726          |
| 0.7496        | 0.1345 | 1000  | 0.7444          |
| 0.7243        | 0.2018 | 1500  | 0.7296          |
| 0.7178        | 0.2691 | 2000  | 0.7197          |
| 0.7077        | 0.3363 | 2500  | 0.7127          |
| 0.6992        | 0.4036 | 3000  | 0.7066          |
| 0.6992        | 0.4708 | 3500  | 0.7012          |
| 0.6945        | 0.5381 | 4000  | 0.6965          |
| 0.6879        | 0.6054 | 4500  | 0.6920          |
| 0.6901        | 0.6726 | 5000  | 0.6879          |
| 0.6759        | 0.7399 | 5500  | 0.6844          |
| 0.6752        | 0.8072 | 6000  | 0.6812          |
| 0.6826        | 0.8744 | 6500  | 0.6783          |
| 0.6804        | 0.9417 | 7000  | 0.6758          |
| 0.6131        | 1.0089 | 7500  | 0.6764          |
| 0.6012        | 1.0762 | 8000  | 0.6758          |
| 0.6136        | 1.1435 | 8500  | 0.6751          |
| 0.6127        | 1.2107 | 9000  | 0.6747          |
| 0.6076        | 1.2780 | 9500  | 0.6745          |
| 0.6033        | 1.3453 | 10000 | 0.6744          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1