---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-1.5B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 32e5aa89-b903-4d0d-906f-719a8b00f1ff
  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>

# 32e5aa89-b903-4d0d-906f-719a8b00f1ff

This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0850

## 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: 0.000207
- 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        | 0.0002 | 1    | 0.6174          |
| 0.12          | 0.0114 | 50   | 0.1566          |
| 0.1155        | 0.0229 | 100  | 0.1270          |
| 0.0906        | 0.0343 | 150  | 0.1307          |
| 0.1028        | 0.0457 | 200  | 0.1006          |
| 0.078         | 0.0572 | 250  | 0.1092          |
| 0.0861        | 0.0686 | 300  | 0.0948          |
| 0.0929        | 0.0801 | 350  | 0.0887          |
| 0.0727        | 0.0915 | 400  | 0.0884          |
| 0.0695        | 0.1029 | 450  | 0.0853          |
| 0.0689        | 0.1144 | 500  | 0.0850          |


### Framework versions

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