---
library_name: peft
license: llama3
base_model: scb10x/llama-3-typhoon-v1.5-8b-instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 06fe8c1a-11ca-43de-8849-53bc60389e04
  results: []
---

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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# 06fe8c1a-11ca-43de-8849-53bc60389e04

This model is a fine-tuned version of [scb10x/llama-3-typhoon-v1.5-8b-instruct](https://huggingface.co/scb10x/llama-3-typhoon-v1.5-8b-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2733

## 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: 0.000217
- train_batch_size: 4
- eval_batch_size: 4
- seed: 170
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0004 | 1    | 1.6572          |
| 0.3887        | 0.0178 | 50   | 0.5777          |
| 0.4069        | 0.0357 | 100  | 0.6546          |
| 0.3688        | 0.0535 | 150  | 0.5131          |
| 0.4015        | 0.0713 | 200  | 0.5132          |
| 0.2953        | 0.0892 | 250  | 0.4764          |
| 0.2395        | 0.1070 | 300  | 0.3887          |
| 0.2984        | 0.1248 | 350  | 0.3598          |
| 0.1899        | 0.1427 | 400  | 0.3352          |
| 0.1957        | 0.1605 | 450  | 0.2770          |
| 0.1991        | 0.1783 | 500  | 0.2733          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1