---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2-0.5B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: ab37478f-15bb-4d01-970f-78a9c6215753
  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>

# ab37478f-15bb-4d01-970f-78a9c6215753

This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7255

## 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: 0.000205
- train_batch_size: 4
- eval_batch_size: 4
- seed: 50
- 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        | 0.0000 | 1    | 4.5647          |
| 3.2376        | 0.0023 | 50   | 3.3136          |
| 3.173         | 0.0045 | 100  | 3.0686          |
| 3.3612        | 0.0068 | 150  | 2.9804          |
| 3.3344        | 0.0090 | 200  | 2.9288          |
| 2.9887        | 0.0113 | 250  | 2.8600          |
| 3.2181        | 0.0135 | 300  | 2.8021          |
| 3.2327        | 0.0158 | 350  | 2.7587          |
| 3.1479        | 0.0181 | 400  | 2.7355          |
| 3.1241        | 0.0203 | 450  | 2.7267          |
| 2.8884        | 0.0226 | 500  | 2.7255          |


### Framework versions

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