---
librar_yname: transformers
license: other
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
  - llama-factory
  - freeze
  - generated_from_trainer
model-index:
  - name: output
    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. -->

# output

This model is a fine-tuned version of Qwen2.5-1.5B-Instruct on the alpaca_zh_demo dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9959

## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 2
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 3.0
  - mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0102        | 1.1111 | 500  | 1.7723          |
| 0.5375        | 2.2222 | 1000 | 1.9768          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.3.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.3