|
--- |
|
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: 0.0644 |
|
- Mse: 0.0644 |
|
- Mae: 0.2027 |
|
- R Squared: 0.2813 |
|
|
|
## 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: 2 |
|
- 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 | 0.0663 | 0.2045 | 0.2606 | |
|
| 0.0648 | 1.4019 | 900 | 0.0649 | 0.0649 | 0.2039 | 0.2764 | |
|
| 0.0652 | 1.5576 | 1000 | 0.0644 | 0.0644 | 0.2027 | 0.2813 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.13.2 |
|
- Transformers 4.45.2 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.3 |
