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

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: 0.7216

## 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: 3e-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_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8741        | 0.0448 | 100  | 0.8600          |
| 0.8038        | 0.0897 | 200  | 0.8095          |
| 0.7937        | 0.1345 | 300  | 0.7789          |
| 0.7712        | 0.1794 | 400  | 0.7644          |
| 0.7393        | 0.2242 | 500  | 0.7565          |
| 0.7458        | 0.2691 | 600  | 0.7506          |
| 0.7694        | 0.3139 | 700  | 0.7458          |
| 0.713         | 0.3587 | 800  | 0.7422          |
| 0.7347        | 0.4036 | 900  | 0.7387          |
| 0.7243        | 0.4484 | 1000 | 0.7356          |
| 0.7161        | 0.4933 | 1100 | 0.7331          |
| 0.7247        | 0.5381 | 1200 | 0.7308          |
| 0.7477        | 0.5830 | 1300 | 0.7288          |
| 0.7429        | 0.6278 | 1400 | 0.7273          |
| 0.7317        | 0.6726 | 1500 | 0.7256          |
| 0.7226        | 0.7175 | 1600 | 0.7243          |
| 0.695         | 0.7623 | 1700 | 0.7234          |
| 0.7167        | 0.8072 | 1800 | 0.7226          |
| 0.686         | 0.8520 | 1900 | 0.7221          |
| 0.7214        | 0.8969 | 2000 | 0.7218          |
| 0.7358        | 0.9417 | 2100 | 0.7216          |
| 0.7259        | 0.9865 | 2200 | 0.7216          |


### Framework versions

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