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---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- generated_from_trainer
model-index:
- name: qwen_checkpoints
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. -->
# qwen_checkpoints
This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0618
- Mse: 0.0618
- Mae: 0.1983
- R Squared: 0.3107
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mae | Mse | R Squared |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:|
| 0.0856 | 0.1558 | 100 | 0.0878 | 0.2351 | 0.0878 | 0.0207 |
| 0.0843 | 0.3115 | 200 | 0.0803 | 0.2314 | 0.0803 | 0.1045 |
| 0.0851 | 0.4673 | 300 | 0.0882 | 0.2278 | 0.0882 | 0.0168 |
| 0.0676 | 0.6231 | 400 | 0.0716 | 0.2183 | 0.0716 | 0.2014 |
| 0.0737 | 0.7788 | 500 | 0.0691 | 0.2164 | 0.0691 | 0.2291 |
| 0.0694 | 0.9346 | 600 | 0.0696 | 0.2157 | 0.0696 | 0.2242 |
| 0.0569 | 1.0903 | 700 | 0.0661 | 0.2049 | 0.0661 | 0.2627 |
| 0.0589 | 1.2461 | 800 | 0.0663 | 0.2045 | 0.0663 | 0.2606 |
| 0.0648 | 1.4019 | 900 | 0.0649 | 0.2039 | 0.0649 | 0.2764 |
| 0.0652 | 1.5576 | 1000 | 0.0644 | 0.2027 | 0.0644 | 0.2813 |
| 0.0657 | 1.7134 | 1100 | 0.0649 | 0.0649 | 0.2082 | 0.2763 |
| 0.0577 | 1.8692 | 1200 | 0.0639 | 0.0639 | 0.2022 | 0.2869 |
| 0.0564 | 2.0249 | 1300 | 0.0636 | 0.0636 | 0.2006 | 0.2902 |
| 0.0613 | 2.1807 | 1400 | 0.0633 | 0.0633 | 0.1989 | 0.2939 |
| 0.0596 | 2.3364 | 1500 | 0.0624 | 0.0624 | 0.1999 | 0.3036 |
| 0.0547 | 2.4922 | 1600 | 0.0621 | 0.0621 | 0.1985 | 0.3076 |
| 0.0554 | 2.6480 | 1700 | 0.0620 | 0.0620 | 0.1974 | 0.3087 |
| 0.0581 | 2.8037 | 1800 | 0.0618 | 0.0618 | 0.1983 | 0.3107 |
| 0.0653 | 2.9595 | 1900 | 0.0618 | 0.0618 | 0.1983 | 0.3107 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3 |