---
library_name: peft
tags:
- generated_from_trainer
base_model: Qwen/Qwen2.5-1.5B-Instruct
model-index:
- name: miniclaus-qw1.5B-UNAMGS
  results: []
---

# miniclaus-qw1.5B-UNAMGS

[<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)

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7193

## 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:
- train_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1641        | 0.0007 | 1    | 0.8514          |
| 0.9246        | 0.0503 | 76   | 0.7921          |
| 0.8791        | 0.1006 | 152  | 0.7727          |
| 0.8507        | 0.1509 | 228  | 0.7611          |
| 0.8376        | 0.2012 | 304  | 0.7534          |
| 0.793         | 0.2515 | 380  | 0.7467          |
| 0.7834        | 0.3018 | 456  | 0.7421          |
| 0.7807        | 0.3521 | 532  | 0.7384          |
| 0.764         | 0.4023 | 608  | 0.7359          |
| 0.7738        | 0.4526 | 684  | 0.7320          |
| 0.7425        | 0.5029 | 760  | 0.7300          |
| 0.7519        | 0.5532 | 836  | 0.7279          |
| 0.7461        | 0.6035 | 912  | 0.7255          |
| 0.7489        | 0.6538 | 988  | 0.7245          |
| 0.7614        | 0.7041 | 1064 | 0.7222          |
| 0.7576        | 0.7544 | 1140 | 0.7222          |
| 0.7303        | 0.8047 | 1216 | 0.7209          |
| 0.7332        | 0.8550 | 1292 | 0.7199          |
| 0.7541        | 0.9053 | 1368 | 0.7202          |
| 0.7369        | 0.9556 | 1444 | 0.7193          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1