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---
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
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