---
library_name: peft
license: other
base_model: NousResearch/Meta-Llama-3-8B-Alternate-Tokenizer
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 17ddfec3-de9b-4a13-aab4-36976da7fb83
  results: []
---

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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>

# 17ddfec3-de9b-4a13-aab4-36976da7fb83

This model is a fine-tuned version of [NousResearch/Meta-Llama-3-8B-Alternate-Tokenizer](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Alternate-Tokenizer) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1896

## 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: 0.000204
- 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        | 0.0001 | 1    | 2.1742          |
| 2.0712        | 0.0026 | 50   | 1.7819          |
| 1.8743        | 0.0052 | 100  | 1.7514          |
| 1.8739        | 0.0079 | 150  | 1.8120          |
| 2.1821        | 0.0105 | 200  | 1.6885          |
| 1.7126        | 0.0131 | 250  | 1.4994          |
| 1.8793        | 0.0157 | 300  | 1.4284          |
| 1.8794        | 0.0183 | 350  | 1.3096          |
| 1.6114        | 0.0210 | 400  | 1.2151          |
| 1.8403        | 0.0236 | 450  | 1.1930          |
| 1.8475        | 0.0262 | 500  | 1.1896          |


### Framework versions

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