| | --- |
| | 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 |
