---
library_name: peft
license: other
base_model: unsloth/Llama-3.2-3B-Instruct
tags:
- llama-factory
- lora
- unsloth
- generated_from_trainer
model-index:
- name: llm3br256
  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. -->

# llm3br256

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 gommt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0206

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.232         | 0.1613 | 25   | 0.2193          |
| 0.1524        | 0.3226 | 50   | 0.1507          |
| 0.115         | 0.4839 | 75   | 0.1165          |
| 0.0875        | 0.6452 | 100  | 0.1004          |
| 0.092         | 0.8065 | 125  | 0.0909          |
| 0.1077        | 0.9677 | 150  | 0.0900          |
| 0.0688        | 1.1290 | 175  | 0.0778          |
| 0.0682        | 1.2903 | 200  | 0.0723          |
| 0.0621        | 1.4516 | 225  | 0.0668          |
| 0.0668        | 1.6129 | 250  | 0.0646          |
| 0.0672        | 1.7742 | 275  | 0.0587          |
| 0.0484        | 1.9355 | 300  | 0.0544          |
| 0.0468        | 2.0968 | 325  | 0.0516          |
| 0.0438        | 2.2581 | 350  | 0.0503          |
| 0.0364        | 2.4194 | 375  | 0.0493          |
| 0.0365        | 2.5806 | 400  | 0.0460          |
| 0.0469        | 2.7419 | 425  | 0.0432          |
| 0.027         | 2.9032 | 450  | 0.0379          |
| 0.026         | 3.0645 | 475  | 0.0356          |
| 0.0223        | 3.2258 | 500  | 0.0357          |
| 0.0228        | 3.3871 | 525  | 0.0352          |
| 0.0199        | 3.5484 | 550  | 0.0336          |
| 0.0227        | 3.7097 | 575  | 0.0308          |
| 0.0207        | 3.8710 | 600  | 0.0292          |
| 0.0125        | 4.0323 | 625  | 0.0304          |
| 0.0146        | 4.1935 | 650  | 0.0279          |
| 0.0126        | 4.3548 | 675  | 0.0283          |
| 0.0141        | 4.5161 | 700  | 0.0270          |
| 0.0133        | 4.6774 | 725  | 0.0254          |
| 0.0098        | 4.8387 | 750  | 0.0250          |
| 0.0093        | 5.0    | 775  | 0.0234          |
| 0.0073        | 5.1613 | 800  | 0.0247          |
| 0.0087        | 5.3226 | 825  | 0.0254          |
| 0.0102        | 5.4839 | 850  | 0.0242          |
| 0.0077        | 5.6452 | 875  | 0.0230          |
| 0.0085        | 5.8065 | 900  | 0.0230          |
| 0.0069        | 5.9677 | 925  | 0.0213          |
| 0.0056        | 6.1290 | 950  | 0.0226          |
| 0.0063        | 6.2903 | 975  | 0.0224          |
| 0.0055        | 6.4516 | 1000 | 0.0227          |
| 0.0067        | 6.6129 | 1025 | 0.0229          |
| 0.0052        | 6.7742 | 1050 | 0.0224          |
| 0.008         | 6.9355 | 1075 | 0.0219          |
| 0.0053        | 7.0968 | 1100 | 0.0227          |
| 0.0049        | 7.2581 | 1125 | 0.0220          |
| 0.0059        | 7.4194 | 1150 | 0.0218          |
| 0.0045        | 7.5806 | 1175 | 0.0215          |
| 0.0058        | 7.7419 | 1200 | 0.0206          |
| 0.0047        | 7.9032 | 1225 | 0.0207          |
| 0.0043        | 8.0645 | 1250 | 0.0223          |
| 0.0046        | 8.2258 | 1275 | 0.0218          |
| 0.0036        | 8.3871 | 1300 | 0.0225          |
| 0.0034        | 8.5484 | 1325 | 0.0216          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3