---
library_name: peft
license: llama3
base_model: elyza/Llama-3-ELYZA-JP-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: babac902-74e0-4bde-a637-dafeb8b8482d
  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. -->

[<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>

# babac902-74e0-4bde-a637-dafeb8b8482d

This model is a fine-tuned version of [elyza/Llama-3-ELYZA-JP-8B](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1751

## 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: 0.000206
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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    | 3.2539          |
| 2.3008        | 0.0181 | 50   | 2.5440          |
| 2.1869        | 0.0362 | 100  | 2.7194          |
| 2.2702        | 0.0544 | 150  | 2.7566          |
| 2.2174        | 0.0725 | 200  | 2.4249          |
| 2.17          | 0.0906 | 250  | 2.3869          |
| 2.2559        | 0.1087 | 300  | 2.2846          |
| 2.2087        | 0.1268 | 350  | 2.2185          |
| 2.2695        | 0.1450 | 400  | 2.1837          |
| 2.0524        | 0.1631 | 450  | 2.1747          |
| 2.0353        | 0.1812 | 500  | 2.1751          |


### Framework versions

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