---
base_model: meta-llama/Llama-3.2-3B-Instruct
library_name: peft
license: llama3.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llama3.2-3b-hard
  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. -->

# llama3.2-3b-hard

This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0052

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.6035        | 0.5202  | 100  | 2.2469          |
| 2.412         | 1.0403  | 200  | 2.1836          |
| 2.3523        | 1.5605  | 300  | 2.1436          |
| 2.3063        | 2.0806  | 400  | 2.1116          |
| 2.24          | 2.6008  | 500  | 2.0822          |
| 2.2205        | 3.1209  | 600  | 2.0610          |
| 2.169         | 3.6411  | 700  | 2.0429          |
| 2.1232        | 4.1612  | 800  | 2.0338          |
| 2.1088        | 4.6814  | 900  | 2.0237          |
| 2.0885        | 5.2016  | 1000 | 2.0192          |
| 2.0604        | 5.7217  | 1100 | 2.0126          |
| 2.0353        | 6.2419  | 1200 | 2.0069          |
| 1.9994        | 6.7620  | 1300 | 2.0035          |
| 1.9972        | 7.2822  | 1400 | 2.0057          |
| 1.9674        | 7.8023  | 1500 | 1.9955          |
| 1.9455        | 8.3225  | 1600 | 2.0008          |
| 1.9392        | 8.8427  | 1700 | 2.0010          |
| 1.9339        | 9.3628  | 1800 | 2.0055          |
| 1.9034        | 9.8830  | 1900 | 1.9982          |
| 1.8877        | 10.4031 | 2000 | 2.0052          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.45.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1