---
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 akoul_whitehorseliquidity_25c dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0008

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.0078        | 0.0808 | 25   | 0.0079          |
| 0.0119        | 0.1616 | 50   | 0.0051          |
| 0.0036        | 0.2424 | 75   | 0.0032          |
| 0.004         | 0.3232 | 100  | 0.0025          |
| 0.0019        | 0.4040 | 125  | 0.0020          |
| 0.0021        | 0.4848 | 150  | 0.0018          |
| 0.0016        | 0.5657 | 175  | 0.0016          |
| 0.0013        | 0.6465 | 200  | 0.0015          |
| 0.0017        | 0.7273 | 225  | 0.0015          |
| 0.0015        | 0.8081 | 250  | 0.0014          |
| 0.0023        | 0.8889 | 275  | 0.0013          |
| 0.0012        | 0.9697 | 300  | 0.0013          |
| 0.0011        | 1.0505 | 325  | 0.0013          |
| 0.0011        | 1.1313 | 350  | 0.0013          |
| 0.0009        | 1.2121 | 375  | 0.0012          |
| 0.0015        | 1.2929 | 400  | 0.0011          |
| 0.0025        | 1.3737 | 425  | 0.0011          |
| 0.0016        | 1.4545 | 450  | 0.0011          |
| 0.001         | 1.5354 | 475  | 0.0011          |
| 0.0007        | 1.6162 | 500  | 0.0011          |
| 0.0008        | 1.6970 | 525  | 0.0011          |
| 0.001         | 1.7778 | 550  | 0.0010          |
| 0.0007        | 1.8586 | 575  | 0.0010          |
| 0.0013        | 1.9394 | 600  | 0.0009          |
| 0.0007        | 2.0202 | 625  | 0.0010          |
| 0.0006        | 2.1010 | 650  | 0.0009          |
| 0.0007        | 2.1818 | 675  | 0.0009          |
| 0.001         | 2.2626 | 700  | 0.0009          |
| 0.0015        | 2.3434 | 725  | 0.0009          |
| 0.0012        | 2.4242 | 750  | 0.0010          |
| 0.0012        | 2.5051 | 775  | 0.0009          |
| 0.0015        | 2.5859 | 800  | 0.0010          |
| 0.0011        | 2.6667 | 825  | 0.0009          |
| 0.0007        | 2.7475 | 850  | 0.0009          |
| 0.0009        | 2.8283 | 875  | 0.0009          |
| 0.0009        | 2.9091 | 900  | 0.0008          |
| 0.001         | 2.9899 | 925  | 0.0009          |
| 0.0006        | 3.0707 | 950  | 0.0009          |
| 0.0006        | 3.1515 | 975  | 0.0009          |
| 0.0007        | 3.2323 | 1000 | 0.0009          |
| 0.0004        | 3.3131 | 1025 | 0.0009          |


### Framework versions

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